cps_data/Imputation Project/P22250 Full Imputation RF vs mnlogitOLS.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import statsmodels.api as sm\n",
    "import statsmodels.formula.api as smf\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "from statsmodels import regression\n",
    "from sklearn import ensemble\n",
    "from sklearn import linear_model\n",
    "from sklearn import metrics\n",
    "from sklearn import model_selection\n",
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remove aggregate rows, replace NaN with 0\n",
    "\n",
    "puf = pd.read_csv('puf2011.csv')\n",
    "\n",
    "puf = puf[(puf['RECID'] != 999996) &\n",
    "          (puf['RECID'] != 999997) &\n",
    "          (puf['RECID'] != 999998) &\n",
    "          (puf['RECID'] != 999999)\n",
    "         ]\n",
    "           \n",
    "puf = puf.fillna(0)\n",
    "\n",
    "# Constant column\n",
    "\n",
    "puf['constant'] = 1\n",
    "\n",
    "#  MARS to K - 1 dummies\n",
    "\n",
    "puf[['MARS2', 'MARS3', 'MARS4']] = pd.get_dummies(puf['MARS'], drop_first = True)\n",
    "\n",
    "# E19800 and E20100 combined in CPS\n",
    "\n",
    "puf['E19800_E20100'] = puf['E19800'] + puf['E20100']\n",
    "\n",
    "# Categorical dependent variable for 1st stage\n",
    "\n",
    "puf['sign'] = np.where(puf['P22250'] == 0, 'zer', np.where(puf['P22250'] > 0, 'pos', 'neg'))\n",
    "\n",
    "# All variables shared between puf and cps, except for E00650 (colinear w/E00600)\n",
    "\n",
    "predictors =  [\n",
    "              'DSI', 'EIC', 'MARS2', 'MARS3', 'MARS4', 'XTOT', \n",
    "              'E00200', 'E00300', 'E00400', 'E00600', 'E00800', 'E00900', \n",
    "              'E01400', 'E01500', 'E01700', 'E02100', 'E02300', 'E02400', \n",
    "              'E03150', 'E03210', 'E03240', 'E03270', 'E03300', 'E17500', \n",
    "              'E18400', 'E18500', 'E19200', 'E19800_E20100','E20400', \n",
    "              'E32800', 'F2441', 'N24', 'E01100'\n",
    "              ]\n",
    "\n",
    "discretes = ['DSI', 'EIC', 'MARS2', 'MARS3', 'MARS4', 'XTOT', 'F2441', 'N24']\n",
    "\n",
    "# Create log columns of continuous predictors/response \n",
    "\n",
    "logs = []\n",
    "\n",
    "for i in predictors + ['P22250']:\n",
    "   \n",
    "    if i not in discretes:\n",
    "        \n",
    "        if puf[i].min() >= 1:\n",
    "            \n",
    "            puf['log_' + i] = np.log(puf[i])\n",
    "       \n",
    "        puf['log_' + i] = np.log(puf[i] - puf[i].min() + 1)\n",
    "          \n",
    "        logs.append('log_' + i)\n",
    "\n",
    "keep = ['RECID', 'AGIR1', 'sign', 'P22250', 'constant'] + predictors + logs\n",
    "\n",
    "puf = puf[keep]\n",
    "\n",
    "np.random.seed(100)\n",
    "\n",
    "train, test = train_test_split(puf.copy(), test_size=0.2)\n",
    "\n",
    "# Drop two negative outliers\n",
    "\n",
    "train = train.drop(labels = [46928, 143309])\n",
    "\n",
    "# Sub-df's where P22250 > 0 or < 0 pos or neg for 2nd stage imputation\n",
    "\n",
    "pos_train = train.copy()[train.copy()['P22250'] > 0]\n",
    "neg_train = train.copy()[train.copy()['P22250'] < 0]\n",
    "\n",
    "pos_test =  test.copy()[test.copy()['P22250'] > 0]\n",
    "neg_test =  test.copy()[test.copy()['P22250'] < 0]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## One-stage prediction: Random Forests\n",
    "Using rf.predict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=-1)]: Done  42 tasks      | elapsed:  1.3min\n",
      "[Parallel(n_jobs=-1)]: Done 100 out of 100 | elapsed:  3.0min finished\n",
      "[Parallel(n_jobs=4)]: Done  42 tasks      | elapsed:    0.2s\n",
      "[Parallel(n_jobs=4)]: Done 100 out of 100 | elapsed:    0.6s finished\n"
     ]
    }
   ],
   "source": [
    "# 100 estimators\n",
    "N_ESTIMATORS = 100\n",
    "rf = ensemble.RandomForestRegressor(n_estimators=N_ESTIMATORS, \n",
    "                                    min_samples_leaf=1, random_state=3, \n",
    "                                    verbose=True, \n",
    "                                    n_jobs=-1)  # Use maximum number of cores.\n",
    "\n",
    "rf.fit(train[predictors], train['P22250'])\n",
    "\n",
    "rf_predictions = rf.predict(test[predictors])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "rf_preds = array of estimators"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "rf_preds = []\n",
    "for estimator in rf.estimators_:\n",
    "    rf_preds.append(estimator.predict(test[predictors]))\n",
    "rf_preds = np.array(rf_preds).transpose()  # One row per record."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## One-Stage Validation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Log-loss\n",
    "\n",
    "We can calculate the RF model's predicted probability for each sign (and thus its log-loss) using the % of estimators predicting that sign for each observation.\n",
    "\n",
    "Note: `metrics.log_loss()` assumes that the order of the columns of predicted probabilities correspond to their categories' alphabetical order. Our categories are `'neg'`, `'zer'` and `'pos'`, which have the alphabetical order of `'neg'`, `'pos'`, `'zer'`, thus they appear in that order in `rf_pred_proba` as `[preds_neg, preds_pos, preds_zer]`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6897766709507555"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "preds_neg = np.sum(rf_preds < 0, axis=1) / 100\n",
    "preds_zer = np.sum(rf_preds == 0, axis=1) / 100\n",
    "preds_pos = np.sum(rf_preds > 0, axis=1) / 100\n",
    "\n",
    "rf_pred_proba = list(map(list, zip(*[preds_neg, preds_pos, preds_zer])))\n",
    "\n",
    "metrics.log_loss(test['sign'], rf_pred_proba)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### RMSE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "411117.31955911306"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(test['P22250'] - rf_predictions).pow(2).mean()** 0.5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Two-stage Prediction: mnlogit + OLS\n",
    "### 1st stage: mnlogit "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimization terminated successfully.\n",
      "         Current function value: 0.577166\n",
      "         Iterations 9\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>MNLogit Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>         <td>y</td>        <th>  No. Observations:  </th>  <td>131026</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>              <td>MNLogit</td>     <th>  Df Residuals:      </th>  <td>130960</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>               <td>MLE</td>       <th>  Df Model:          </th>  <td>    64</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>          <td>Fri, 10 Aug 2018</td> <th>  Pseudo R-squ.:     </th>  <td>0.2373</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>              <td>16:06:26</td>     <th>  Log-Likelihood:    </th> <td> -75624.</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>converged:</th>           <td>True</td>       <th>  LL-Null:           </th> <td> -99159.</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th> </th>                      <td> </td>        <th>  LLR p-value:       </th>  <td> 0.000</td> \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "   <th>y=sign[pos]</th>     <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th>     <td>   -0.1281</td> <td>    0.034</td> <td>   -3.727</td> <td> 0.000</td> <td>   -0.195</td> <td>   -0.061</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>DSI</th>           <td>    0.1601</td> <td>    0.147</td> <td>    1.092</td> <td> 0.275</td> <td>   -0.127</td> <td>    0.447</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>EIC</th>           <td>   -0.2173</td> <td>    0.118</td> <td>   -1.848</td> <td> 0.065</td> <td>   -0.448</td> <td>    0.013</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>MARS2</th>         <td>   -0.0308</td> <td>    0.041</td> <td>   -0.752</td> <td> 0.452</td> <td>   -0.111</td> <td>    0.050</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>MARS3</th>         <td>   -0.0040</td> <td>    0.080</td> <td>   -0.051</td> <td> 0.959</td> <td>   -0.160</td> <td>    0.152</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>MARS4</th>         <td>    0.0132</td> <td>    0.079</td> <td>    0.167</td> <td> 0.868</td> <td>   -0.142</td> <td>    0.169</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>XTOT</th>          <td>   -0.0009</td> <td>    0.019</td> <td>   -0.047</td> <td> 0.963</td> <td>   -0.037</td> <td>    0.035</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E00200</th>        <td>-1.787e-08</td> <td> 7.39e-09</td> <td>   -2.419</td> <td> 0.016</td> <td>-3.23e-08</td> <td>-3.39e-09</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E00300</th>        <td> 9.886e-08</td> <td>  3.2e-08</td> <td>    3.086</td> <td> 0.002</td> <td> 3.61e-08</td> <td> 1.62e-07</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E00400</th>        <td>-1.294e-07</td> <td> 5.07e-08</td> <td>   -2.550</td> <td> 0.011</td> <td>-2.29e-07</td> <td>   -3e-08</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E00600</th>        <td> -1.73e-08</td> <td> 1.76e-08</td> <td>   -0.980</td> <td> 0.327</td> <td>-5.19e-08</td> <td> 1.73e-08</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E00800</th>        <td>-1.384e-05</td> <td> 1.03e-05</td> <td>   -1.350</td> <td> 0.177</td> <td>-3.39e-05</td> <td> 6.26e-06</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E00900</th>        <td>-3.552e-08</td> <td> 3.51e-08</td> <td>   -1.011</td> <td> 0.312</td> <td>-1.04e-07</td> <td> 3.34e-08</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E01400</th>        <td>-5.094e-09</td> <td> 6.17e-08</td> <td>   -0.083</td> <td> 0.934</td> <td>-1.26e-07</td> <td> 1.16e-07</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E01500</th>        <td>-5.403e-09</td> <td> 2.02e-08</td> <td>   -0.267</td> <td> 0.789</td> <td> -4.5e-08</td> <td> 3.42e-08</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E01700</th>        <td>-7.231e-08</td> <td> 1.64e-07</td> <td>   -0.441</td> <td> 0.659</td> <td>-3.93e-07</td> <td> 2.49e-07</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E02100</th>        <td> 2.644e-08</td> <td> 1.16e-07</td> <td>    0.228</td> <td> 0.819</td> <td>-2.01e-07</td> <td> 2.53e-07</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E02300</th>        <td>-1.062e-05</td> <td> 6.17e-06</td> <td>   -1.721</td> <td> 0.085</td> <td>-2.27e-05</td> <td> 1.48e-06</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E02400</th>        <td>-3.856e-06</td> <td> 9.18e-07</td> <td>   -4.200</td> <td> 0.000</td> <td>-5.66e-06</td> <td>-2.06e-06</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E03150</th>        <td> 5.022e-07</td> <td> 6.84e-06</td> <td>    0.073</td> <td> 0.941</td> <td>-1.29e-05</td> <td> 1.39e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E03210</th>        <td>-6.289e-05</td> <td>    0.000</td> <td>   -0.623</td> <td> 0.533</td> <td>   -0.000</td> <td>    0.000</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E03240</th>        <td>-3.404e-07</td> <td> 1.68e-07</td> <td>   -2.029</td> <td> 0.042</td> <td>-6.69e-07</td> <td>-1.16e-08</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E03270</th>        <td> 5.258e-06</td> <td> 1.77e-06</td> <td>    2.963</td> <td> 0.003</td> <td> 1.78e-06</td> <td> 8.74e-06</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E03300</th>        <td>-3.957e-07</td> <td> 4.66e-07</td> <td>   -0.849</td> <td> 0.396</td> <td>-1.31e-06</td> <td> 5.17e-07</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E17500</th>        <td>-8.072e-07</td> <td> 7.62e-07</td> <td>   -1.060</td> <td> 0.289</td> <td> -2.3e-06</td> <td> 6.86e-07</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E18400</th>        <td> 3.184e-09</td> <td> 3.42e-08</td> <td>    0.093</td> <td> 0.926</td> <td>-6.39e-08</td> <td> 7.02e-08</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E18500</th>        <td>-3.136e-07</td> <td> 4.36e-07</td> <td>   -0.720</td> <td> 0.472</td> <td>-1.17e-06</td> <td>  5.4e-07</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E19200</th>        <td> 3.845e-07</td> <td> 1.36e-07</td> <td>    2.824</td> <td> 0.005</td> <td> 1.18e-07</td> <td> 6.51e-07</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E19800_E20100</th> <td>-2.573e-09</td> <td>  2.3e-08</td> <td>   -0.112</td> <td> 0.911</td> <td>-4.77e-08</td> <td> 4.26e-08</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E20400</th>        <td>-3.691e-08</td> <td> 1.02e-07</td> <td>   -0.361</td> <td> 0.718</td> <td>-2.37e-07</td> <td> 1.64e-07</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E32800</th>        <td>-6.243e-06</td> <td> 2.82e-05</td> <td>   -0.222</td> <td> 0.825</td> <td>-6.15e-05</td> <td>  4.9e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>F2441</th>         <td>    0.0010</td> <td>    0.058</td> <td>    0.018</td> <td> 0.986</td> <td>   -0.113</td> <td>    0.115</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>N24</th>           <td>    0.0457</td> <td>    0.020</td> <td>    2.242</td> <td> 0.025</td> <td>    0.006</td> <td>    0.086</td>\n",
       "</tr>\n",
       "<tr>\n",
       "   <th>y=sign[zer]</th>     <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th>     <td>    3.0321</td> <td>    0.028</td> <td>  107.842</td> <td> 0.000</td> <td>    2.977</td> <td>    3.087</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>DSI</th>           <td>    0.9075</td> <td>    0.107</td> <td>    8.481</td> <td> 0.000</td> <td>    0.698</td> <td>    1.117</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>EIC</th>           <td>    1.3177</td> <td>    0.074</td> <td>   17.715</td> <td> 0.000</td> <td>    1.172</td> <td>    1.463</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>MARS2</th>         <td>   -0.6360</td> <td>    0.034</td> <td>  -18.458</td> <td> 0.000</td> <td>   -0.704</td> <td>   -0.568</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>MARS3</th>         <td>   -0.3229</td> <td>    0.069</td> <td>   -4.680</td> <td> 0.000</td> <td>   -0.458</td> <td>   -0.188</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>MARS4</th>         <td>    0.4112</td> <td>    0.060</td> <td>    6.797</td> <td> 0.000</td> <td>    0.293</td> <td>    0.530</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>XTOT</th>          <td>   -0.1057</td> <td>    0.017</td> <td>   -6.218</td> <td> 0.000</td> <td>   -0.139</td> <td>   -0.072</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E00200</th>        <td>-8.375e-07</td> <td> 2.25e-08</td> <td>  -37.160</td> <td> 0.000</td> <td>-8.82e-07</td> <td>-7.93e-07</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E00300</th>        <td>-2.924e-06</td> <td> 1.81e-07</td> <td>  -16.191</td> <td> 0.000</td> <td>-3.28e-06</td> <td>-2.57e-06</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E00400</th>        <td>-3.313e-06</td> <td> 2.22e-07</td> <td>  -14.956</td> <td> 0.000</td> <td>-3.75e-06</td> <td>-2.88e-06</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E00600</th>        <td> -1.28e-06</td> <td>    1e-07</td> <td>  -12.795</td> <td> 0.000</td> <td>-1.48e-06</td> <td>-1.08e-06</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E00800</th>        <td>-1.901e-05</td> <td> 5.84e-06</td> <td>   -3.253</td> <td> 0.001</td> <td>-3.05e-05</td> <td>-7.55e-06</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E00900</th>        <td> 7.825e-09</td> <td> 4.14e-08</td> <td>    0.189</td> <td> 0.850</td> <td>-7.32e-08</td> <td> 8.89e-08</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E01400</th>        <td>-1.379e-06</td> <td> 1.38e-07</td> <td>   -9.966</td> <td> 0.000</td> <td>-1.65e-06</td> <td>-1.11e-06</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E01500</th>        <td> -3.46e-07</td> <td> 2.92e-08</td> <td>  -11.847</td> <td> 0.000</td> <td>-4.03e-07</td> <td>-2.89e-07</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E01700</th>        <td>-3.175e-07</td> <td> 2.12e-07</td> <td>   -1.501</td> <td> 0.133</td> <td>-7.32e-07</td> <td> 9.71e-08</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E02100</th>        <td> 2.102e-07</td> <td>  1.3e-07</td> <td>    1.617</td> <td> 0.106</td> <td>-4.45e-08</td> <td> 4.65e-07</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E02300</th>        <td> 2.953e-05</td> <td> 4.44e-06</td> <td>    6.657</td> <td> 0.000</td> <td> 2.08e-05</td> <td> 3.82e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E02400</th>        <td>-1.557e-05</td> <td> 8.66e-07</td> <td>  -17.982</td> <td> 0.000</td> <td>-1.73e-05</td> <td>-1.39e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E03150</th>        <td>-4.886e-05</td> <td> 6.17e-06</td> <td>   -7.917</td> <td> 0.000</td> <td> -6.1e-05</td> <td>-3.68e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E03210</th>        <td>    0.0008</td> <td>  6.9e-05</td> <td>   10.871</td> <td> 0.000</td> <td>    0.001</td> <td>    0.001</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E03240</th>        <td>     7e-08</td> <td> 2.93e-07</td> <td>    0.239</td> <td> 0.811</td> <td>-5.05e-07</td> <td> 6.45e-07</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E03270</th>        <td>-2.533e-05</td> <td> 1.92e-06</td> <td>  -13.166</td> <td> 0.000</td> <td>-2.91e-05</td> <td>-2.16e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E03300</th>        <td>-1.135e-05</td> <td> 6.77e-07</td> <td>  -16.772</td> <td> 0.000</td> <td>-1.27e-05</td> <td>   -1e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E17500</th>        <td>-5.357e-06</td> <td> 1.06e-06</td> <td>   -5.076</td> <td> 0.000</td> <td>-7.42e-06</td> <td>-3.29e-06</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E18400</th>        <td>-7.802e-07</td> <td> 1.28e-07</td> <td>   -6.077</td> <td> 0.000</td> <td>-1.03e-06</td> <td>-5.29e-07</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E18500</th>        <td>-3.401e-05</td> <td>    1e-06</td> <td>  -33.976</td> <td> 0.000</td> <td> -3.6e-05</td> <td> -3.2e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E19200</th>        <td>-5.089e-07</td> <td> 3.67e-07</td> <td>   -1.388</td> <td> 0.165</td> <td>-1.23e-06</td> <td>  2.1e-07</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E19800_E20100</th> <td>-1.675e-08</td> <td> 8.39e-08</td> <td>   -0.200</td> <td> 0.842</td> <td>-1.81e-07</td> <td> 1.48e-07</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E20400</th>        <td>-4.657e-05</td> <td> 1.15e-06</td> <td>  -40.479</td> <td> 0.000</td> <td>-4.88e-05</td> <td>-4.43e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E32800</th>        <td>    0.0001</td> <td> 2.36e-05</td> <td>    5.563</td> <td> 0.000</td> <td> 8.49e-05</td> <td>    0.000</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>F2441</th>         <td>   -0.1777</td> <td>    0.049</td> <td>   -3.591</td> <td> 0.000</td> <td>   -0.275</td> <td>   -0.081</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>N24</th>           <td>    0.1079</td> <td>    0.019</td> <td>    5.747</td> <td> 0.000</td> <td>    0.071</td> <td>    0.145</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                          MNLogit Regression Results                          \n",
       "==============================================================================\n",
       "Dep. Variable:                      y   No. Observations:               131026\n",
       "Model:                        MNLogit   Df Residuals:                   130960\n",
       "Method:                           MLE   Df Model:                           64\n",
       "Date:                Fri, 10 Aug 2018   Pseudo R-squ.:                  0.2373\n",
       "Time:                        16:06:26   Log-Likelihood:                -75624.\n",
       "converged:                       True   LL-Null:                       -99159.\n",
       "                                        LLR p-value:                     0.000\n",
       "=================================================================================\n",
       "  y=sign[pos]       coef    std err          z      P>|z|      [0.025      0.975]\n",
       "---------------------------------------------------------------------------------\n",
       "Intercept        -0.1281      0.034     -3.727      0.000      -0.195      -0.061\n",
       "DSI               0.1601      0.147      1.092      0.275      -0.127       0.447\n",
       "EIC              -0.2173      0.118     -1.848      0.065      -0.448       0.013\n",
       "MARS2            -0.0308      0.041     -0.752      0.452      -0.111       0.050\n",
       "MARS3            -0.0040      0.080     -0.051      0.959      -0.160       0.152\n",
       "MARS4             0.0132      0.079      0.167      0.868      -0.142       0.169\n",
       "XTOT             -0.0009      0.019     -0.047      0.963      -0.037       0.035\n",
       "E00200        -1.787e-08   7.39e-09     -2.419      0.016   -3.23e-08   -3.39e-09\n",
       "E00300         9.886e-08    3.2e-08      3.086      0.002    3.61e-08    1.62e-07\n",
       "E00400        -1.294e-07   5.07e-08     -2.550      0.011   -2.29e-07      -3e-08\n",
       "E00600         -1.73e-08   1.76e-08     -0.980      0.327   -5.19e-08    1.73e-08\n",
       "E00800        -1.384e-05   1.03e-05     -1.350      0.177   -3.39e-05    6.26e-06\n",
       "E00900        -3.552e-08   3.51e-08     -1.011      0.312   -1.04e-07    3.34e-08\n",
       "E01400        -5.094e-09   6.17e-08     -0.083      0.934   -1.26e-07    1.16e-07\n",
       "E01500        -5.403e-09   2.02e-08     -0.267      0.789    -4.5e-08    3.42e-08\n",
       "E01700        -7.231e-08   1.64e-07     -0.441      0.659   -3.93e-07    2.49e-07\n",
       "E02100         2.644e-08   1.16e-07      0.228      0.819   -2.01e-07    2.53e-07\n",
       "E02300        -1.062e-05   6.17e-06     -1.721      0.085   -2.27e-05    1.48e-06\n",
       "E02400        -3.856e-06   9.18e-07     -4.200      0.000   -5.66e-06   -2.06e-06\n",
       "E03150         5.022e-07   6.84e-06      0.073      0.941   -1.29e-05    1.39e-05\n",
       "E03210        -6.289e-05      0.000     -0.623      0.533      -0.000       0.000\n",
       "E03240        -3.404e-07   1.68e-07     -2.029      0.042   -6.69e-07   -1.16e-08\n",
       "E03270         5.258e-06   1.77e-06      2.963      0.003    1.78e-06    8.74e-06\n",
       "E03300        -3.957e-07   4.66e-07     -0.849      0.396   -1.31e-06    5.17e-07\n",
       "E17500        -8.072e-07   7.62e-07     -1.060      0.289    -2.3e-06    6.86e-07\n",
       "E18400         3.184e-09   3.42e-08      0.093      0.926   -6.39e-08    7.02e-08\n",
       "E18500        -3.136e-07   4.36e-07     -0.720      0.472   -1.17e-06     5.4e-07\n",
       "E19200         3.845e-07   1.36e-07      2.824      0.005    1.18e-07    6.51e-07\n",
       "E19800_E20100 -2.573e-09    2.3e-08     -0.112      0.911   -4.77e-08    4.26e-08\n",
       "E20400        -3.691e-08   1.02e-07     -0.361      0.718   -2.37e-07    1.64e-07\n",
       "E32800        -6.243e-06   2.82e-05     -0.222      0.825   -6.15e-05     4.9e-05\n",
       "F2441             0.0010      0.058      0.018      0.986      -0.113       0.115\n",
       "N24               0.0457      0.020      2.242      0.025       0.006       0.086\n",
       "---------------------------------------------------------------------------------\n",
       "  y=sign[zer]       coef    std err          z      P>|z|      [0.025      0.975]\n",
       "---------------------------------------------------------------------------------\n",
       "Intercept         3.0321      0.028    107.842      0.000       2.977       3.087\n",
       "DSI               0.9075      0.107      8.481      0.000       0.698       1.117\n",
       "EIC               1.3177      0.074     17.715      0.000       1.172       1.463\n",
       "MARS2            -0.6360      0.034    -18.458      0.000      -0.704      -0.568\n",
       "MARS3            -0.3229      0.069     -4.680      0.000      -0.458      -0.188\n",
       "MARS4             0.4112      0.060      6.797      0.000       0.293       0.530\n",
       "XTOT             -0.1057      0.017     -6.218      0.000      -0.139      -0.072\n",
       "E00200        -8.375e-07   2.25e-08    -37.160      0.000   -8.82e-07   -7.93e-07\n",
       "E00300        -2.924e-06   1.81e-07    -16.191      0.000   -3.28e-06   -2.57e-06\n",
       "E00400        -3.313e-06   2.22e-07    -14.956      0.000   -3.75e-06   -2.88e-06\n",
       "E00600         -1.28e-06      1e-07    -12.795      0.000   -1.48e-06   -1.08e-06\n",
       "E00800        -1.901e-05   5.84e-06     -3.253      0.001   -3.05e-05   -7.55e-06\n",
       "E00900         7.825e-09   4.14e-08      0.189      0.850   -7.32e-08    8.89e-08\n",
       "E01400        -1.379e-06   1.38e-07     -9.966      0.000   -1.65e-06   -1.11e-06\n",
       "E01500         -3.46e-07   2.92e-08    -11.847      0.000   -4.03e-07   -2.89e-07\n",
       "E01700        -3.175e-07   2.12e-07     -1.501      0.133   -7.32e-07    9.71e-08\n",
       "E02100         2.102e-07    1.3e-07      1.617      0.106   -4.45e-08    4.65e-07\n",
       "E02300         2.953e-05   4.44e-06      6.657      0.000    2.08e-05    3.82e-05\n",
       "E02400        -1.557e-05   8.66e-07    -17.982      0.000   -1.73e-05   -1.39e-05\n",
       "E03150        -4.886e-05   6.17e-06     -7.917      0.000    -6.1e-05   -3.68e-05\n",
       "E03210            0.0008    6.9e-05     10.871      0.000       0.001       0.001\n",
       "E03240             7e-08   2.93e-07      0.239      0.811   -5.05e-07    6.45e-07\n",
       "E03270        -2.533e-05   1.92e-06    -13.166      0.000   -2.91e-05   -2.16e-05\n",
       "E03300        -1.135e-05   6.77e-07    -16.772      0.000   -1.27e-05      -1e-05\n",
       "E17500        -5.357e-06   1.06e-06     -5.076      0.000   -7.42e-06   -3.29e-06\n",
       "E18400        -7.802e-07   1.28e-07     -6.077      0.000   -1.03e-06   -5.29e-07\n",
       "E18500        -3.401e-05      1e-06    -33.976      0.000    -3.6e-05    -3.2e-05\n",
       "E19200        -5.089e-07   3.67e-07     -1.388      0.165   -1.23e-06     2.1e-07\n",
       "E19800_E20100 -1.675e-08   8.39e-08     -0.200      0.842   -1.81e-07    1.48e-07\n",
       "E20400        -4.657e-05   1.15e-06    -40.479      0.000   -4.88e-05   -4.43e-05\n",
       "E32800            0.0001   2.36e-05      5.563      0.000    8.49e-05       0.000\n",
       "F2441            -0.1777      0.049     -3.591      0.000      -0.275      -0.081\n",
       "N24               0.1079      0.019      5.747      0.000       0.071       0.145\n",
       "=================================================================================\n",
       "\"\"\""
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Formula = sign ~ DSI + EIC + ... + F2441 + N24\n",
    "# It turns out that only 1.3% of E01100 is non-zero, which could be why \n",
    "# including it as a predictor breaks mnlogit. E01100 thus excluded.\n",
    "\n",
    "predictors_mnl = predictors[:-1]\n",
    "formula = 'sign ~ ' + ' + '.join(predictors_mnl)\n",
    "mnl_fit = smf.mnlogit(formula = formula, data = train).fit()\n",
    "summary = mnl_fit.summary()\n",
    "summary"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Extracting probabilities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>neg</th>\n",
       "      <th>pos</th>\n",
       "      <th>zero</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>43632</th>\n",
       "      <td>0.009440</td>\n",
       "      <td>0.007075</td>\n",
       "      <td>0.983485</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55268</th>\n",
       "      <td>0.150469</td>\n",
       "      <td>0.135993</td>\n",
       "      <td>0.713538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155007</th>\n",
       "      <td>0.403581</td>\n",
       "      <td>0.321199</td>\n",
       "      <td>0.275220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46437</th>\n",
       "      <td>0.061226</td>\n",
       "      <td>0.050625</td>\n",
       "      <td>0.888149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30152</th>\n",
       "      <td>0.143453</td>\n",
       "      <td>0.121501</td>\n",
       "      <td>0.735047</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             neg       pos      zero\n",
       "43632   0.009440  0.007075  0.983485\n",
       "55268   0.150469  0.135993  0.713538\n",
       "155007  0.403581  0.321199  0.275220\n",
       "46437   0.061226  0.050625  0.888149\n",
       "30152   0.143453  0.121501  0.735047"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# mnlogit.fit.predict() bug causes columns to lose labels. However according to the documentation \n",
    "# column 0 = omitted category (which is 'neg' as it is the first alphabetically). We can infer that\n",
    "# the most likely column, column 2, is 'zer', thus column 1 = 'pos'\n",
    "\n",
    "mnl_pred_proba = mnl_fit.predict(test[predictors_mnl])\n",
    "mnl_pred_proba.rename(columns={0: 'neg', 1: 'pos', 2: 'zero'}, inplace = True)\n",
    "\n",
    "# Note that columns are alphabetically ordered, so this will work for metrics.log_loss()\n",
    "\n",
    "mnl_pred_proba.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Stochastic sign imputation function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Arguments = 'runif': a random uniform in [0,1], and 'probs': a vector of predicted probabilities for each sign. \n",
    "# Output = predicted sign if associated CDF value > runif.\n",
    "# probs[0] = P(neg), probs[1] = P(pos), probs[2] = P(zer)\n",
    "\n",
    "def stoch_imp(runif, probs):\n",
    "    \n",
    "    if runif < probs[0]:\n",
    "        return ('neg')\n",
    "    \n",
    "    elif runif < probs[0] + probs[1]:\n",
    "        return ('pos')\n",
    "    \n",
    "    else:\n",
    "        return ('zer')\n",
    "\n",
    "# Creates vector of runifs the length of puf, to be used in each imputation.\n",
    "\n",
    "np.random.seed(1995)\n",
    "runifs = np.random.uniform(size = len(test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "mnl_pred_sign = []\n",
    "\n",
    "count = 0\n",
    "\n",
    "for i in runifs:\n",
    "    probs = mnl_pred_proba.iloc[count]\n",
    "    mnl_pred_sign.append(stoch_imp(i, probs))\n",
    "    count += 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Sign imputation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "test['sign_p'] = mnl_pred_sign"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2nd stage: OLS\n",
    "Regressing on log(P22250) using (now) correctly log-transformed continuous predictors"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Positive data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>OLS Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>       <td>log_P22250</td>    <th>  R-squared:         </th>  <td>   0.041</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>                   <td>OLS</td>       <th>  Adj. R-squared:    </th>  <td>   0.040</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>             <td>Least Squares</td>  <th>  F-statistic:       </th>  <td>   35.48</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>             <td>Fri, 10 Aug 2018</td> <th>  Prob (F-statistic):</th>  <td>8.55e-128</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                 <td>16:06:30</td>     <th>  Log-Likelihood:    </th>  <td>  61122.</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>No. Observations:</th>      <td> 15800</td>      <th>  AIC:               </th> <td>-1.222e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Residuals:</th>          <td> 15780</td>      <th>  BIC:               </th> <td>-1.221e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Model:</th>              <td>    19</td>      <th>                     </th>      <td> </td>    \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>      <td>nonrobust</td>    <th>                     </th>      <td> </td>    \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "          <td></td>             <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>constant</th>          <td>   18.6419</td> <td>    0.000</td> <td> 1.16e+05</td> <td> 0.000</td> <td>   18.642</td> <td>   18.642</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>MARS2</th>             <td>   -0.0005</td> <td>    0.000</td> <td>   -4.188</td> <td> 0.000</td> <td>   -0.001</td> <td>   -0.000</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>F2441</th>             <td>   -0.0002</td> <td>    0.000</td> <td>   -1.768</td> <td> 0.077</td> <td>   -0.000</td> <td>  2.5e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>N24</th>               <td>    0.0003</td> <td> 4.79e-05</td> <td>    5.454</td> <td> 0.000</td> <td>    0.000</td> <td>    0.000</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>log_E00200</th>        <td>-3.606e-05</td> <td> 8.61e-06</td> <td>   -4.187</td> <td> 0.000</td> <td>-5.29e-05</td> <td>-1.92e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>log_E00300</th>        <td>    0.0002</td> <td>  1.5e-05</td> <td>   12.893</td> <td> 0.000</td> <td>    0.000</td> <td>    0.000</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>log_E00400</th>        <td>-3.266e-05</td> <td> 1.04e-05</td> <td>   -3.148</td> <td> 0.002</td> <td> -5.3e-05</td> <td>-1.23e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>log_E00600</th>        <td> 9.789e-05</td> <td> 1.58e-05</td> <td>    6.210</td> <td> 0.000</td> <td>  6.7e-05</td> <td>    0.000</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E00900</th>            <td>-3.534e-10</td> <td> 1.37e-10</td> <td>   -2.575</td> <td> 0.010</td> <td>-6.22e-10</td> <td>-8.43e-11</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>log_E01500</th>        <td>-1.876e-05</td> <td> 8.44e-06</td> <td>   -2.224</td> <td> 0.026</td> <td>-3.53e-05</td> <td>-2.23e-06</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E02400</th>            <td>-6.391e-09</td> <td> 3.58e-09</td> <td>   -1.785</td> <td> 0.074</td> <td>-1.34e-08</td> <td> 6.26e-10</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>log_E03240</th>        <td>-5.125e-05</td> <td> 1.52e-05</td> <td>   -3.365</td> <td> 0.001</td> <td>-8.11e-05</td> <td>-2.14e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>E03270</th>            <td> 2.709e-08</td> <td> 6.82e-09</td> <td>    3.975</td> <td> 0.000</td> <td> 1.37e-08</td> <td> 4.04e-08</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>log_E03300</th>        <td>-3.966e-05</td> <td> 1.37e-05</td> <td>   -2.904</td> <td> 0.004</td> <td>-6.64e-05</td> <td>-1.29e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>log_E17500</th>        <td>-3.875e-05</td> <td> 1.87e-05</td> <td>   -2.077</td> <td> 0.038</td> <td>-7.53e-05</td> <td>-2.18e-06</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>log_E18400</th>        <td> 2.361e-05</td> <td> 1.02e-05</td> <td>    2.307</td> <td> 0.021</td> <td> 3.55e-06</td> <td> 4.37e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>log_E18500</th>        <td>-8.303e-05</td> <td> 1.69e-05</td> <td>   -4.920</td> <td> 0.000</td> <td>   -0.000</td> <td>-4.99e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>log_E19200</th>        <td> 6.695e-05</td> <td> 1.12e-05</td> <td>    5.960</td> <td> 0.000</td> <td> 4.49e-05</td> <td>  8.9e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>log_E19800_E20100</th> <td> 3.368e-05</td> <td> 1.62e-05</td> <td>    2.082</td> <td> 0.037</td> <td> 1.97e-06</td> <td> 6.54e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>log_E20400</th>        <td> 4.084e-05</td> <td> 1.19e-05</td> <td>    3.418</td> <td> 0.001</td> <td> 1.74e-05</td> <td> 6.43e-05</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Omnibus:</th>       <td>38405.648</td> <th>  Durbin-Watson:     </th>   <td>   1.998</td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Omnibus):</th>  <td> 0.000</td>   <th>  Jarque-Bera (JB):  </th> <td>661684037.771</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Skew:</th>           <td>25.403</td>   <th>  Prob(JB):          </th>   <td>    0.00</td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Kurtosis:</th>      <td>1004.253</td>  <th>  Cond. No.          </th>   <td>1.24e+06</td>   \n",
       "</tr>\n",
       "</table><br/><br/>Warnings:<br/>[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.<br/>[2] The condition number is large, 1.24e+06. This might indicate that there are<br/>strong multicollinearity or other numerical problems."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                            OLS Regression Results                            \n",
       "==============================================================================\n",
       "Dep. Variable:             log_P22250   R-squared:                       0.041\n",
       "Model:                            OLS   Adj. R-squared:                  0.040\n",
       "Method:                 Least Squares   F-statistic:                     35.48\n",
       "Date:                Fri, 10 Aug 2018   Prob (F-statistic):          8.55e-128\n",
       "Time:                        16:06:30   Log-Likelihood:                 61122.\n",
       "No. Observations:               15800   AIC:                        -1.222e+05\n",
       "Df Residuals:                   15780   BIC:                        -1.221e+05\n",
       "Df Model:                          19                                         \n",
       "Covariance Type:            nonrobust                                         \n",
       "=====================================================================================\n",
       "                        coef    std err          t      P>|t|      [0.025      0.975]\n",
       "-------------------------------------------------------------------------------------\n",
       "constant             18.6419      0.000   1.16e+05      0.000      18.642      18.642\n",
       "MARS2                -0.0005      0.000     -4.188      0.000      -0.001      -0.000\n",
       "F2441                -0.0002      0.000     -1.768      0.077      -0.000     2.5e-05\n",
       "N24                   0.0003   4.79e-05      5.454      0.000       0.000       0.000\n",
       "log_E00200        -3.606e-05   8.61e-06     -4.187      0.000   -5.29e-05   -1.92e-05\n",
       "log_E00300            0.0002    1.5e-05     12.893      0.000       0.000       0.000\n",
       "log_E00400        -3.266e-05   1.04e-05     -3.148      0.002    -5.3e-05   -1.23e-05\n",
       "log_E00600         9.789e-05   1.58e-05      6.210      0.000     6.7e-05       0.000\n",
       "E00900            -3.534e-10   1.37e-10     -2.575      0.010   -6.22e-10   -8.43e-11\n",
       "log_E01500        -1.876e-05   8.44e-06     -2.224      0.026   -3.53e-05   -2.23e-06\n",
       "E02400            -6.391e-09   3.58e-09     -1.785      0.074   -1.34e-08    6.26e-10\n",
       "log_E03240        -5.125e-05   1.52e-05     -3.365      0.001   -8.11e-05   -2.14e-05\n",
       "E03270             2.709e-08   6.82e-09      3.975      0.000    1.37e-08    4.04e-08\n",
       "log_E03300        -3.966e-05   1.37e-05     -2.904      0.004   -6.64e-05   -1.29e-05\n",
       "log_E17500        -3.875e-05   1.87e-05     -2.077      0.038   -7.53e-05   -2.18e-06\n",
       "log_E18400         2.361e-05   1.02e-05      2.307      0.021    3.55e-06    4.37e-05\n",
       "log_E18500        -8.303e-05   1.69e-05     -4.920      0.000      -0.000   -4.99e-05\n",
       "log_E19200         6.695e-05   1.12e-05      5.960      0.000    4.49e-05     8.9e-05\n",
       "log_E19800_E20100  3.368e-05   1.62e-05      2.082      0.037    1.97e-06    6.54e-05\n",
       "log_E20400         4.084e-05   1.19e-05      3.418      0.001    1.74e-05    6.43e-05\n",
       "==============================================================================\n",
       "Omnibus:                    38405.648   Durbin-Watson:                   1.998\n",
       "Prob(Omnibus):                  0.000   Jarque-Bera (JB):        661684037.771\n",
       "Skew:                          25.403   Prob(JB):                         0.00\n",
       "Kurtosis:                    1004.253   Cond. No.                     1.24e+06\n",
       "==============================================================================\n",
       "\n",
       "Warnings:\n",
       "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
       "[2] The condition number is large, 1.24e+06. This might indicate that there are\n",
       "strong multicollinearity or other numerical problems.\n",
       "\"\"\""
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Predictors included are those with p values <= 0.1\n",
    "\n",
    "ols_pos_predictors = [\n",
    "                      'constant', 'MARS2', 'F2441', 'N24', 'log_E00200',\n",
    "                      'log_E00300', 'log_E00400', 'log_E00600', 'E00900',\n",
    "                      'log_E01500', 'E02400', 'log_E03240', 'E03270',\n",
    "                      'log_E03300', 'log_E17500', 'log_E18400', 'log_E18500',\n",
    "                      'log_E19200', 'log_E19800_E20100', 'log_E20400'\n",
    "                     ]\n",
    "\n",
    "ols_pos_fit = sm.OLS(pos_train['log_P22250'], pos_train[ols_pos_predictors]).fit()\n",
    "summary = ols_pos_fit.summary()\n",
    "\n",
    "summary"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Negative data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>OLS Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>       <td>log_P22250</td>    <th>  R-squared:         </th>  <td>   0.013</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>                   <td>OLS</td>       <th>  Adj. R-squared:    </th>  <td>   0.012</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>             <td>Least Squares</td>  <th>  F-statistic:       </th>  <td>   18.64</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>             <td>Fri, 10 Aug 2018</td> <th>  Prob (F-statistic):</th>  <td>5.25e-44</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                 <td>16:06:30</td>     <th>  Log-Likelihood:    </th>  <td>  71202.</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>No. Observations:</th>      <td> 18598</td>      <th>  AIC:               </th> <td>-1.424e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Residuals:</th>          <td> 18584</td>      <th>  BIC:               </th> <td>-1.423e+05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Model:</th>              <td>    13</td>      <th>                     </th>      <td> </td>    \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>      <td>nonrobust</td>    <th>                     </th>      <td> </td>    \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "          <td></td>             <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>constant</th>          <td>   18.4684</td> <td>    0.067</td> <td>  274.766</td> <td> 0.000</td> <td>   18.337</td> <td>   18.600</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>MARS3</th>             <td>   -0.0011</td> <td>    0.000</td> <td>   -4.056</td> <td> 0.000</td> <td>   -0.002</td> <td>   -0.001</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>MARS4</th>             <td>   -0.0006</td> <td>    0.000</td> <td>   -2.159</td> <td> 0.031</td> <td>   -0.001</td> <td>-5.24e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>log_E00200</th>        <td> 3.726e-05</td> <td> 7.59e-06</td> <td>    4.908</td> <td> 0.000</td> <td> 2.24e-05</td> <td> 5.21e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>log_E00300</th>        <td>-9.291e-05</td> <td> 1.47e-05</td> <td>   -6.320</td> <td> 0.000</td> <td>   -0.000</td> <td>-6.41e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>log_E00400</th>        <td> 3.854e-05</td> <td>  9.9e-06</td> <td>    3.892</td> <td> 0.000</td> <td> 1.91e-05</td> <td>  5.8e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>log_E00600</th>        <td>   -0.0001</td> <td> 1.55e-05</td> <td>   -6.960</td> <td> 0.000</td> <td>   -0.000</td> <td>-7.76e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>log_E00900</th>        <td>    0.0101</td> <td>    0.004</td> <td>    2.600</td> <td> 0.009</td> <td>    0.002</td> <td>    0.018</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>log_E03210</th>        <td>   -0.0001</td> <td>  6.4e-05</td> <td>   -1.741</td> <td> 0.082</td> <td>   -0.000</td> <td>  1.4e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>log_E03270</th>        <td> 3.825e-05</td> <td> 1.07e-05</td> <td>    3.584</td> <td> 0.000</td> <td> 1.73e-05</td> <td> 5.92e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>log_E17500</th>        <td>  4.68e-05</td> <td> 1.74e-05</td> <td>    2.692</td> <td> 0.007</td> <td> 1.27e-05</td> <td> 8.09e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>log_E18400</th>        <td>  2.08e-05</td> <td> 9.56e-06</td> <td>    2.176</td> <td> 0.030</td> <td> 2.06e-06</td> <td> 3.95e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>log_E19200</th>        <td>-4.709e-05</td> <td> 9.63e-06</td> <td>   -4.892</td> <td> 0.000</td> <td> -6.6e-05</td> <td>-2.82e-05</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>log_E19800_E20100</th> <td> 3.901e-05</td> <td> 1.34e-05</td> <td>    2.909</td> <td> 0.004</td> <td> 1.27e-05</td> <td> 6.53e-05</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Omnibus:</th>       <td>47463.812</td> <th>  Durbin-Watson:     </th>    <td>   2.004</td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Omnibus):</th>  <td> 0.000</td>   <th>  Jarque-Bera (JB):  </th> <td>1187646059.051</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Skew:</th>           <td>-28.687</td>  <th>  Prob(JB):          </th>    <td>    0.00</td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Kurtosis:</th>      <td>1239.657</td>  <th>  Cond. No.          </th>    <td>4.73e+04</td>   \n",
       "</tr>\n",
       "</table><br/><br/>Warnings:<br/>[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.<br/>[2] The condition number is large, 4.73e+04. This might indicate that there are<br/>strong multicollinearity or other numerical problems."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                            OLS Regression Results                            \n",
       "==============================================================================\n",
       "Dep. Variable:             log_P22250   R-squared:                       0.013\n",
       "Model:                            OLS   Adj. R-squared:                  0.012\n",
       "Method:                 Least Squares   F-statistic:                     18.64\n",
       "Date:                Fri, 10 Aug 2018   Prob (F-statistic):           5.25e-44\n",
       "Time:                        16:06:30   Log-Likelihood:                 71202.\n",
       "No. Observations:               18598   AIC:                        -1.424e+05\n",
       "Df Residuals:                   18584   BIC:                        -1.423e+05\n",
       "Df Model:                          13                                         \n",
       "Covariance Type:            nonrobust                                         \n",
       "=====================================================================================\n",
       "                        coef    std err          t      P>|t|      [0.025      0.975]\n",
       "-------------------------------------------------------------------------------------\n",
       "constant             18.4684      0.067    274.766      0.000      18.337      18.600\n",
       "MARS3                -0.0011      0.000     -4.056      0.000      -0.002      -0.001\n",
       "MARS4                -0.0006      0.000     -2.159      0.031      -0.001   -5.24e-05\n",
       "log_E00200         3.726e-05   7.59e-06      4.908      0.000    2.24e-05    5.21e-05\n",
       "log_E00300        -9.291e-05   1.47e-05     -6.320      0.000      -0.000   -6.41e-05\n",
       "log_E00400         3.854e-05    9.9e-06      3.892      0.000    1.91e-05     5.8e-05\n",
       "log_E00600           -0.0001   1.55e-05     -6.960      0.000      -0.000   -7.76e-05\n",
       "log_E00900            0.0101      0.004      2.600      0.009       0.002       0.018\n",
       "log_E03210           -0.0001    6.4e-05     -1.741      0.082      -0.000     1.4e-05\n",
       "log_E03270         3.825e-05   1.07e-05      3.584      0.000    1.73e-05    5.92e-05\n",
       "log_E17500          4.68e-05   1.74e-05      2.692      0.007    1.27e-05    8.09e-05\n",
       "log_E18400          2.08e-05   9.56e-06      2.176      0.030    2.06e-06    3.95e-05\n",
       "log_E19200        -4.709e-05   9.63e-06     -4.892      0.000    -6.6e-05   -2.82e-05\n",
       "log_E19800_E20100  3.901e-05   1.34e-05      2.909      0.004    1.27e-05    6.53e-05\n",
       "==============================================================================\n",
       "Omnibus:                    47463.812   Durbin-Watson:                   2.004\n",
       "Prob(Omnibus):                  0.000   Jarque-Bera (JB):       1187646059.051\n",
       "Skew:                         -28.687   Prob(JB):                         0.00\n",
       "Kurtosis:                    1239.657   Cond. No.                     4.73e+04\n",
       "==============================================================================\n",
       "\n",
       "Warnings:\n",
       "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
       "[2] The condition number is large, 4.73e+04. This might indicate that there are\n",
       "strong multicollinearity or other numerical problems.\n",
       "\"\"\""
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ols_neg_predictors = [\n",
    "                      'constant', 'MARS3', 'MARS4', 'log_E00200', 'log_E00300',\n",
    "                      'log_E00400', 'log_E00600', 'log_E00900', 'log_E03210',\n",
    "                      'log_E03270', 'log_E17500', 'log_E18400', 'log_E19200',\n",
    "                     'log_E19800_E20100'\n",
    "                     ] \n",
    "ols_neg_fit = sm.OLS(neg_train['log_P22250'], neg_train[ols_neg_predictors]).fit()\n",
    "summary = ols_neg_fit.summary()\n",
    "\n",
    "summary"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Continuous value imputation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# neg/pos_p_test = observations in test predicted to be neg/pos by mnlogit\n",
    "\n",
    "neg_p_test = test.copy()[test.copy()['sign_p'] == 'neg']\n",
    "pos_p_test = test.copy()[test.copy()['sign_p'] == 'pos']\n",
    "\n",
    "log_neg_predictions = ols_neg_fit.predict(neg_p_test[ols_neg_predictors])\n",
    "log_pos_predictions = ols_pos_fit.predict(pos_p_test[ols_pos_predictors])\n",
    "\n",
    "# Transform via e^(Y-hat) + min(P22250) - 1\n",
    "\n",
    "neg_predictions = np.exp(log_neg_predictions) + puf['P22250'].min() - 1\n",
    "pos_predictions = np.exp(log_pos_predictions) + puf['P22250'].min() - 1\n",
    "\n",
    "ols_predictions = pd.concat([neg_predictions, pos_predictions], axis = 0).to_frame()\n",
    "\n",
    "# NaN rows were not in neg_p_test or pos_pos_test, thus they were predicted by mnlogit to be 0\n",
    "\n",
    "test['mnlOLS_p'] = ols_predictions\n",
    "test['mnlOLS_p'] = test['mnlOLS_p'].fillna(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Validation\n",
    "\n",
    "#### Log-loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5836617256539257"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metrics.log_loss(test['sign'], mnl_pred_proba)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### RMSE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "389051.8348869253"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(test['P22250'] - test['mnlOLS_p']).pow(2).mean()**0.5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Predicting 0 and mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# First create a small dataset with the columns of interest\n",
    "test['RF_p'] = rf_predictions\n",
    "data = test.copy()[['AGIR1', 'P22250', 'RF_p', 'mnlOLS_p']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What if we just predicted zero?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "385182.5436336457"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(data['P22250']).pow(2).mean()**0.5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What if we just predicted the mean? (-3291)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "385168.48227679287"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(data['P22250'] - data['P22250'].mean()).pow(2).mean()**0.5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analysis of predictions\n",
    "Below I will compare the predicted distribution of P22250 over AGI between RF, test (actual), and mnl+OLS."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, limiting the y axis to +/- 10,000,000. This cuts out only a few predictions/actual observations but makes the whole thing more visible."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,0.98,'In +/- 10,000,000')"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c1c0efb70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(color_codes=True)\n",
    "plt.figure(figsize=(15,20))\n",
    "\n",
    "plt.subplot(311)\n",
    "plt.title('Random Forests', fontsize = 17)\n",
    "plt.ylim(-10000000, 10000000)\n",
    "sns.regplot(data['AGIR1'], data['RF_p'], fit_reg=False)\n",
    "\n",
    "plt.subplot(312)\n",
    "plt.title('PUF Test', fontsize = 17)\n",
    "plt.ylim(-10000000, 10000000)\n",
    "sns.regplot(data['AGIR1'], data['P22250'], fit_reg=False)\n",
    "\n",
    "plt.subplot(313)\n",
    "plt.title('MNLogit + OLS', fontsize = 17)\n",
    "plt.ylim(-10000000, 10000000)\n",
    "sns.regplot(data['AGIR1'], data['mnlOLS_p'], fit_reg=False)\n",
    "plt.plot([0, 35], [750000, 750000], color='green', linestyle='dashed', linewidth=1)\n",
    "plt.plot([0, 35], [-750000, -750000], color='green', linestyle='dashed', linewidth=1)\n",
    "\n",
    "plt.suptitle('In +/- 10,000,000', fontsize = 25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "+/- 750,000\n",
    "\n",
    "Green lines in mnlogit graph indicate next graph's y-scales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,0.98,'In +/- 750,000')"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c1f5599b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(color_codes=True)\n",
    "plt.figure(figsize=(15,20))\n",
    "\n",
    "plt.subplot(311)\n",
    "plt.title('Random Forests', fontsize = 17)\n",
    "plt.ylim(-750000, 750000)\n",
    "sns.regplot(data['AGIR1'], data['RF_p'], fit_reg=False)\n",
    "\n",
    "plt.subplot(312)\n",
    "plt.title('PUF Test', fontsize = 17)\n",
    "plt.ylim(-750000, 750000)\n",
    "sns.regplot(data['AGIR1'], data['P22250'], fit_reg=False)\n",
    "\n",
    "plt.subplot(313)\n",
    "plt.title('MNLogit + OLS', fontsize = 17)\n",
    "plt.ylim(-750000, 750000)\n",
    "sns.regplot(data['AGIR1'], data['mnlOLS_p'], fit_reg=False)\n",
    "plt.plot([0, 35], [150000, 150000], color='green', linestyle='dashed', linewidth=1)\n",
    "plt.plot([0, 35], [-200000, -200000], color='green', linestyle='dashed', linewidth=1)\n",
    "\n",
    "plt.suptitle('In +/- 750,000', fontsize = 25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[-200000, 150000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,0.98,'In [-200000, 150000]')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c1d1cd898>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(color_codes=True)\n",
    "plt.figure(figsize=(15,20))\n",
    "\n",
    "plt.subplot(311)\n",
    "plt.title('Random Forests', fontsize = 17)\n",
    "plt.ylim(-200000, 150000)\n",
    "sns.regplot(data['AGIR1'], data['RF_p'], fit_reg=False)\n",
    "\n",
    "plt.subplot(312)\n",
    "plt.title('PUF Test', fontsize = 17)\n",
    "plt.ylim(-200000, 150000)\n",
    "sns.regplot(data['AGIR1'], data['P22250'], fit_reg=False)\n",
    "\n",
    "plt.subplot(313)\n",
    "plt.title('MNLogit + OLS', fontsize = 17)\n",
    "plt.ylim(-200000, 150000)\n",
    "sns.regplot(data['AGIR1'], data['mnlOLS_p'], fit_reg=False)\n",
    "plt.plot([0, 35], [10000, 10000], color='green', linestyle='dashed', linewidth=1)\n",
    "plt.plot([0, 35], [-10000, -10000], color='green', linestyle='dashed', linewidth=1)\n",
    "\n",
    "plt.suptitle('In [-200000, 150000]', fontsize = 25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "+/- 10,000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,0.98,'In +/- 10,000')"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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BIhEREREREakYJBIREREREZGKQSIRERERERGpGCQSERERERGRikEiERERERERqRgkEhERERERkYpBIhEREREREakYJBIREREREZGKQSIRERERERGpGCQSERERERGRikEiERERERERqRgkEhERERERkYpBIhEREREREakYJBIREREREZGKQSIRERERERGpGCQSERERERGRikEiERERERERqRgkEhERERERkYpBIhEREREREakYJBIREREREZGKQSIRERERERGpGCQSERERERGRikEiERERERERqRgkEhERERERkYpBIhEREREREakYJBIREREREZGKQSIRERERERGpGCQSERERERGRikEiERERERERqRgkEhERERERkYpBIhEREemmKEpfHwIRESWJ1NcHQERE6W3evHl444034tozMjLQv39/nHXWWbjtttuQmZnZa8c0depUjB49Go8//niv/Z/trVu3Dtdcc03C3xcWFuLTTz/txSM6svfffx8ffPABHnnkkb4+FCIiSgIGiURE1Odyc3Pxl7/8pUObx+PBqlWr8Pzzz+PgwYNYtGhRHx1d37n77rsxZsyYuHabzdYHR5PYc889B7vd3teHQUREScIgkYiI+pwkSZrB0FlnnYXGxkasXLkSCxYsQFZWVh8cXd8pLS3VPC9ERERG4pxEIiIytezsbAiCAEEQ1LaPPvoIV199NcaOHYsRI0bg7LPPxp///GdEIhF1m7KyMrz44ou49957cfrpp2P06NH4xS9+gZ07d3bof/369bjqqqswZswYTJ06Fe+8807cMciyjFdeeQUXXXQRRo8ejcmTJ2PBggXwer3qNosXL8bUqVOxatUqXHTRRRg5ciTOO+88rFq1Crt27cLPf/5zjB49GlOmTMELL7yQtPPj8/nw8MMP45xzzsHIkSNx7rnnYsmSJR3mCF599dW44447cMcdd+CUU07BZZddBlmWoSgKlixZgnPPPRcjRozAlClT8MQTTyAUCqn7BoNBLFy4EGeddZZ6rhctWoRgMAggmpr79ddf4/PPP0dZWRnWrVsHAHjxxRcxffp0jBw5EhMmTMDcuXNRV1eXtMdNRETG4UgiERGZQjgcVv+tKAo8Hg8++ugjvPHGG5g2bZo6J/HTTz/FL3/5S1x22WW46aabEA6H8dZbb+Gpp55CUVERLrnkErWfxx9/HJMnT8YjjzyChoYGPPDAA5g7dy6WL18OAPjuu+9w7bXXYsyYMXjsscfg8Xhw//33o7GxscOxzZ8/H8uWLcO1116Lu+66C9u3b8fixYuxYcMGvPzyy2qqZUNDA+bPn49bb70V+fn5ePjhh3H77bcjPz8fl19+Oa699lo8//zz+NOf/oRRo0Zh1KhRRzwniqJ0OC8xkhT9+g4EArjqqqtQW1uLOXPmYMiQIaioqMBDDz2EXbt24d5771X3effdd3HmmWfiqaeegt/vhyiKWLhwIf75z3/iF7/4BU4//XRs3boVixcvxp49e/DYY48BABYuXIh3330X8+bNQ1FREb7++ms8/vjjEEURt912G5588kncddddsFqtmD9/PoYOHaqO/M6ZMwennXYaampq8Mgjj+DXv/41Xn755S6/JoiIqG8wSCQioj534MABDB8+PK7d7XZj9uzZmDNnjtq2fft2TJ8+HQsWLFDbysvL8fHHH2PdunUdgsRBgwZ1KD5TXV2NxYsXo66uDoWFhXj22Wfhcrnw7LPPwuFwAAAGDx6MK6+8Ut1nx44dePXVV3HTTTfh1ltvBQBMmjQJpaWluO6667Bs2TJcddVVAIC2tjb87ne/w49+9CMA0aBx3rx5uPrqq3HdddcBAE488UScddZZ2LBhw1GDxBtuuEGzvbKyEgCwfPlyVFZWYsmSJZgwYYJ6LqxWK5599llcffXVGDp0KIDoaOhDDz0El8sFANi9ezdeeOEF/PKXv8SvfvUr9XG53W785je/wTXXXIMxY8bgiy++wIgRI9Tzetppp8HhcKipvyeddBIyMzNht9vV1NjPP/8cWVlZuOGGG9T5k7m5udi0aRMikQgsFssRHzcREfUtBolERNTncnNz8dxzzwEAWltb8fzzz6OiogJz587FxRdf3GHbn//85wAAv9+Pqqoq7NmzB1u3bkU4HO6QJgkAp5xySoefBwwYoP4fQDSYmThxohogxvY57rjj1J9j6ZMXXHBBh74mT56MgoICrFu3Tg0SO/+fBQUFANBhXmFeXh4AoLm5+cgnBcDvf//7I85JXLduHfr166cGiDEXX3wxnn32Waxbt04NEgcOHKgGiACwdu1aKIqCs88+u8No5ZQpUyAIAioqKjBmzBhMmDABL774Iq688kpMnToVZ511FmbPnn3E454wYQJefvllzJgxA9OmTcMZZ5yBSZMm4cwzzzzqYyYior7HIJGIiPqcJEkYOXKk+vNpp52Gm266CfPmzUNmZibOOecc9Xcejwf33HMPPvjgA8iyjOLiYowZMwZWqzVurb6MjIwOP4tidCq+LMtqX/n5+XHH43a71X83NTXFtbXfrv28RABwOp1x27UPQtvPrTyakpKSDuels6amJvTr10/zuAB0OLbO28VSatuPvLYXmz84b948DBgwACtWrMCjjz6KRx99FEOHDsXdd9+N8vJyzX3PPfdcPP7443jxxRfx97//HX/9619RUFCA66+/Hj/72c+O8IiJiMgMGCQSEZHpCIKA++67D9OnT8cf/vAHjBs3Tg3m5s6di++++w7PPPMMTj31VDUQ7Dya1hV5eXk4cOBAXHtjYyOOP/54AEBOTg4AoL6+HtnZ2R22279/vzpS1xdycnKwbdu2uPb9+/cDODxqqSX2WJ577jnk5ubG/T62r81mww033IAbbrgBdXV1WL16Nf7yl79gzpw5WLNmTYcAuL3p06dj+vTp8Pl8WLduHZ5//nk8+OCDGDlyJMaNG9ftx0pERL2H1U2JiMiUCgoKcOedd8Lj8XRYpP2LL77A2WefjcmTJ6sB4jfffIODBw+qI4RdNWnSJFRUVHQYcausrER1dbX68/jx4wEAb731Vod9V69ejYMHD+LUU0/t9mNLlvHjx+PAgQNYu3Zth/YVK1YAwBGP7bTTTgMQnQ86cuRI9U9GRgYWLVqEnTt3QpZlzJw5Ew8++CAAoLCwEJdeeil+8pOfoLW1VR1ljY3Qxtxzzz24/PLLAURHVs8++2zMmzcPALBv374kPHIiIjISRxKJiMi0Zs2ahddffx1vvPEGLrvsMpx88skYPXo03n33XYwePRpFRUXYunUrnn76aQiCAL/f363+b775ZnzwwQe49tprcdNNN6GtrQ2PP/54h8XqTzjhBFx66aV49tlnEQqFMHHiROzcuROLFy/GsGHD4uZM9qaZM2fin//8J2699VbccsstKC0txWeffYb//d//xY9//GOUlpYm3PfEE0/EzJkzsWDBAtTU1ODkk09GbW0tFi9ejFAohOHDh0MURYwdOxYvvPAC8vPzMXr0aNTW1mLJkiU45ZRT1DmeOTk52LJlC9auXYuTTjoJEydOxEsvvYS7774b559/PoLBIP72t78hOzsbkydP7q3TQ0REPcQgkYiITEsQBMyfPx+zZs3Cvffei2XLluHBBx/EwoUL8cADDyASiaC4uBhz5szB999/j3fffRfBYLBDkHckxcXFePHFF/Hwww/jzjvvhNPpxHXXXYeVK1d22G7BggUoKSnB66+/jn/84x8oKCjAhRdeiF//+tdx8x57U0ZGBpYuXYrHHnsMzzzzDJqamlBSUqJWJz2a++67D6WlpVi2bBn+53/+B7m5uRg/fjxuvfVWtejOXXfdhaysLLz22mtYvHgxXC4XpkyZgjvuuEPt56c//Sl++9vf4vrrr8cDDzyACy64AA899BCWLFmCd999F4Ig4JRTTsHSpUs154ASEZG5CErnWf5ERERERESUtjgnkYiIiIiIiFQMEomIiIiIiEjVJ0Hi119/jauvvhoAsHv3blx55ZW46qqrMH/+fLUy3ZNPPolLL70UV1xxBTZt2tTtbYmIiIiIiKj7ej1I/Otf/4rf//73CAQCAIAHHngAt956K/75z39CURR8+OGH2LJlCz7//HO89tpreOyxx3Dvvfd2e1siIiIiIiLqvl4PEgcNGoTFixerP2/ZskVdq+mMM87AmjVrsH79epSXl0MQBBx33HGIRCI4ePBgt7YlIiIiIiKi7uv1JTCmTZvWYZFiRVEgCAIAICsrC16vFz6fD7m5ueo2sfbubHu0EtvhcASSZEnmQ+uxGx/8P9Q2tCIiHy40axEFDCjIwjPzzu7DI+s9tz+xClqFdkVRwKJfn9kHR0RH81Xlfix9Z2tc+9XTT8IpZf374IiIqCseXvoldlQ3orklhFBYhlUSkZ1lxdCiPNx59bi+PjzqJXc/VYHKPY2IRBQoUCBAgMUioKwkDw/8srzH/V7ym7cQDsto/40uAJAkEcsfuqDH/b764Ta8+sG2uPbLfjQMl509rEd9/vi3byMQjMS1Z9gsePX+83vUJwBc/tuVaA2E49oz7RJeuX9Gj/u94I4VCX/31qKLetzvRXeuwKEZXB2IIrDikZ71++Pfvo22QPy5ddj1nduf/PHfaG4JxrVnZ9nw4oLzetwvr2ni9fk6iaJ4eDCzpaUF2dnZcDqdaGlp6dDucrm6te3RNDa2JukR6OfMkCAIgCgACqIfpoIAODMsqK/39vXh9Yo8pw11jfGLYBfmOUx/Dtxul+mP0QgrV+9AKBz/rbJy9Q4U5zv64Ii6Jl2fr1TG5yy53Dl2rNvcpv4cDEVwwBPB6cPtSTvPfM7Mr8UfRL7LDq8/hIiswCIKcDmsaGkN6XruFEVB51u+yqF2Pf1W7mqAw26BtzUEWVEgCgJcmVZU7mrocb+hkIy4gwUQDMm6jlUrQIy1G/W+0PWcaQSIsfae9msRBEiiAFlRoCg4dJ0rQBQEXcfa4g8lbNfTr9HXNGb+THS7teOmPq9uetJJJ2HdunUAgE8//RTjxo3DKaecgoqKCsiyjB9++AGyLCM/P79b26aW6JtGsoiwSRZIFhGiIETfUWmifNTAbrVT36v3xAf10fY2zXYiMofq/T7kueyQJBEQoiM8eS47qvf7+vrQqBe5cx3IsEtw5zpQ3N/Z7ucMXf0KCa5dErV31e46L1rbwrCIAqwWERZRQGtbGHvqev66tUral8GJ2qnritxZkKFAVqJxuKwAMhQUubN09ds+664r7V3Fa5p4fT6S+Jvf/AZ/+MMf8Nhjj6G0tBTTpk2DxWLBuHHjcPnll0OWZfzxj3/s9rapJBiOIK/d3TzJIsLlsCIYSnBr5xg0YkgBAKBiUw3qPW1w52agfNRAtZ3Mx53r0Bz91XuBQUTGqvf4kWGXkGGXOrWn78VQOiofNRDLVu3UbNfDJomQZSVuCo1NZ+AVCsuQFQWyrKhZV6IoIBiOT2nsqpJCF3b80BTXZ8mAo2ekHUsEAdCY8aNrrKJfrgOVe5s6tMlytN2MeE0Tr0+CxKKiIrz66qsAgCFDhuCFF16I22bOnDmYM2dOh7bubJtK3LkObNvrQSAYUVMobJKYdh9SI4YUMChMIUZdYJBxNu9qOHQjxg93roM3YtIUL4YI6Hhz1tMSRGFecj4TitxZ2PFDc9wUGr0jSLKiIBI5HMkoQHQ+pY4BpBkTS/Di+9vg9YcQjsjqTfoZE0p0HatRJIuAcCT+AUsWfaO0iU6hnrG5ryrrtdu31eMXPZ+WaRhe08Tr85FEiqY1eHyHJ+FGFAUeX5DpDmRqHP1NLZt3NXT4Aqxr9Ks/8zlLL7wYopiqWi+272tCS1sYBzIkFPV36v48GF5agO+rmxAbSFQAQFYwvFRfv6IgwKIxx03PaNeIIQX4yTnDkv495s7N0ByZ13sjxmIREY7Ej5xKFn3XiwK0A0I9oadfoyAQAPg1itl0hxHHCvCaRguDRBPYtL1Bu32HdjuRWXD0N3VUbKpJ2M7nML3wYogA4O21VXj7syoA0fmCvtaQ+vP5Ewb3uN8tOxsgigLQKYVzy84GXf1aJRGiKEDsFA5YdVaqN+J7zNeqXVzFl6DoSldFNAqrAEA4om96UlaGVfM2O7syAAAgAElEQVTYshxWXf0awYhRzxhe03TEINEEWtpChz/y2t0iSVTBiYiouzgpn9rjxRB9smEfZFmJjszhUDAnCPhkwz5dwVx1fUu0imWnFMjq+pYEe3RNSaELbcEIfO2qmzozrSgpdOrq14g0fKNG0cIJirNopaB2x49OK8aK1bvi5pH+6NRiXf1SamM+owkYVQmMiCjGnaBYAOehEaWn5pYgIvLhOX2KEq0Q6dVYg84Mivo74WsNqccckRX4WkMo6t/zIDGWhl/X6IesHE7D37wrvTK5Bg9wxc1rlCwCBpuwNoYkal8bJ2qnnmOQaAIDCzK71U5E1F1cZoaI2hMNukFd5NYO2vQEcwDw+da6uGUOIrKCz7fW9bjPI6Xh65GokIzeAjNGefWj7xHoVFE/EJLx6kff99ERJTZ+eGG32qnnmG5qApdNHYq/rNiC1rZwdDI2gMwMCZdNHdrXh0ZExwjOQyNKXUakRGY5rPB4A5rtehhVMfSHA63a7Q3a7V1hVBq+NUGBGbMWJPyhQfs8JGrXQ2+YXJifGVe8RjjUTsnFINEknA5rtJyzrMAiCnCacLIwEaU2zkMjSj1GVSY+sSgH2/Z64I3N8RMFuDKtOLEoR9fxGlUxVE6w1oWsYxF1o5aDCSUoJBMKJ6O8SvIlOod6zq1NEhHUKLSjN1D+9392xxWpUQ6165lLS/EYJJpAxaYadWFjqyQidOhNxaqDRERE6c2oysTlowairtGPHKe9w7VHMlLQjbghdahgqmZ7T/X+cjDmDBKNYFQV0kTFf/QWBaJ4DBJNgFUHiYiISItR1wjtU9A9LUEU5iUnjdUox/XL0qyQely/rB73aVQafoJBz4Ttfa39TYLO7T2VaFkOvct1UO9hkGgCRqU7EBERUWoz8hohNuLndrtQX+/V3Z+RLps6FH9f+e3h9Fghmh6bvPoNJo3gekHpwGx8v88DuV38JopA6XHZPe4z1QJlimfOGbRppnzUQLQFwqj3+LG3zod6jx9tgTCrDhIREaU5ViaOGjGkAMOH5MNyKL/UIgoYPiRf16ifUUtgiAlyYBO197UZE0vgznEgM0OCzSoiM0OCO8ehu9iQERKNbpq1KFAq4xk1ibZQBIFgBMFw9O+2EHOriYiI0t2IIQUYW+aGtzWImoYWeFuDGFvmNm1aqFHeXluFtZtrEQzLUBQgGJaxdnMt3l5b1eM+jVoCI8Nq0W63abf3tRFDCjBp1EBk2CwQED3OSSZNPXYkOIeJ2qnnmG5qAivXVMHfFoZFFCAJIhRFgb8tjJVrqkz5BjWiFDcRERHF27yrAesr6+HKtMGVaQMArK+sx+ABrrT67v33f3bHFa6RFX1VLY2a7yklGNWSLOYcm0ml15jXH+pWO/WcOV+taUZrIvaR2vuSUakZREREFM+o0a5UY0RVS3euI0G7vvmeggA1LTbGIgoQzJltmlKvMc517D0cSTQJWVEgywoURBcFNWveulGluImIiCgeK6Abp3zUQM1iOLPOLNXVr6woiHQa9ozIimkDmXqPHwc8frS2hdXr0MwMCaJZo1qDMFOuIwaJJpDnsmNfbNRQiN4NiUQU5OXb+/bANPDLioiIEoldZDX6gshz2tL+IisZWAHdOFW1XvhaQ1AUBVAABQp8rSFU1Xp1vW4DCUY324LhHvdpJG9rEC1th49NAdDSFoa3NdB3B9XLYplyMbFMOQBp+xnGdFMTyMqQYLEcTkMQBMBiEZCVYb4Y3qjUDCIiSm3tpyMoisLpCEnC6qbG+WTDPoiiAMkiwiqJkCwiRFHAJxv26eo3UfHBtqA5ixI2eoPdaj8WpVLKbW9hkGgCwbCM/OwMZNgl2CQLMuwS8rMzEAybLy+BX1ZERKSFF1nGGDGkALPOLEVhngOiIKAwz4FZZ5am3eiGw56gqmWC9q7wJSh20qKzCEqqzZvrnBp7tPZjETPl4plvqCoNuXMdkBv9cNglWCURobB8qN18o3OxL6VoznYb3LkZTCciIiJeZBkotuh9qjBibld2lg1tAX+HJe8FADlZPZ+a43RY4WuNDwizHNYe92kkURQgawRuZq1jkUqY1h2PQaIJlI8a2CEPun27GaXalxURERmPF1lR6V78YvOuBrzw/jb4/CGEIzLqGv2oqvVi9jnDdJ0Hq0VE5/BIASBZeh4gnXXy8Xj7syrNdjOyJAgSO1dSpe5LtWvx3sB0UxNov1Du3v2+tF0ol4iIUhenI3CZKCC69rPHG0A4LAMKEA7L8HgDWLmmSle/Dc3aI9KJ2rvi/AmDMbQoB+GIjGBYRjgiY2hRTo/XXTRaooBYT6AMGJPKm2qY1h2PI4kmELvr2BaMAEp0YnPFphpTLmJKRESkpf10BE9LEIV56TeKxmWijFv7OZCg6Eui9q54e20Vtlc3dVjkfnt1E95eW6UrUBSAuFHPWLsegZDcrfauslpE+BF/Hq0W840lCYL23M5krNbBTLmOGCSawMo1VTjQ5Icce4+HomWSV66p4ouVkiLd05+IqHfELrLcbhfq6719fTi9zqh5mfwMN0aiKqafbNinK0h0OqzwahS/cWbqm+uolWp6pPauataYl3mk9r5UkG3Hgab4pTkKss23bFyqM98tgjS0s8Z7OEA8RJaj7UR6Mf2JiKh3GLFMVKp9hhe5ndrt/bXbu8pu1U59tNvMV900L0HAkudiIEOpg0GiCYTD2mkCidqJuoNl6YmI4m3e1YBnVmzGn/7xBZ5ZsTkpQVf5qIHwB8Ko9/hR09CCeo8f/kBY17zMik01aPIFUL3fhz11XlTv96HJFzDtZ/iMiSXIzJAQkRWEIjIisoLMDAkzJpTo6jfbaYPY6apVFPVXN9Wit7ppbUNrt9qp6w4mWLsxUTv1HNNNiY5xLEtPRNTR5l0NePH9bfC2q8C5u9aLn+iswAnEzzvTO1VqW7UHTb7DF8CyoqDJF8T31U06ezaOzWqB3RYtBCNZRNgSjAJ2R0mhC1CgPmeSRYTLYcWgwp6PUBpV3TSY4CZ/iDf/dTMq5RZgWndnDBJNwGIREI5olDTWWa2KCGBZeiKizlau2Y1G7+F5TeGwjEZvACvX7tZ1UVixqQYZdgkZdimuvaf9tvrDmu16UyKNUrGpBg67BEcSzwEQHaWta/THnVs9o7SxeYefbNiHFn8IWQ4rzjr5eN3VTRMVrtFLFBE3PSnWTvrE0rpjYmndANI2UGSQaAJ2mwVhjS8Bu41PD+nHtX+IKJUZcXe/ut6n3b5fu72rjMjckBVFM+BIwsCJIYzKXhkxpABVtd64gE7va2HwABeGHp+jvr4GD3Dp6g+ILm4fMWDRe4ddQovG9WKmXV96LB1O6/a2hiArCkRBgCvTmlaViTtjFGICiYfOmZZA+rUvS1/vaYM7NyPtUyiIUkW6pz+l2t19IzI3HDZJs1JmMtawi72+Gn1B5DltSXl9GZW9snlXA9ZX1sOVaYMr0wYAWF9Zr2u5MKNeX5JFO0jUu56hmCB5ORnLPySbkUtVGOH76iZ42qV1RxQFHpOndRuNQaIJGLXuDVEM1/4hSj2pFiAZwah1B4vcWdilUUG8yJ3V4z4BYzI3cpw2zSqcOVm2HvcJRF9fL7y/DT5/CJGIgn0WAVW1XszWOS/TqOyVik018AfC8LWbk+h06BvpMer1lWjEUO9IYmtAO/W4tU27vS9ZLaLm3Ewzrr0IAN5W7cI3idrTgTmfqXSjdavlSO1ERHTMY2Vi41IXZ0wcjFyXHZIkAgIgSSJyXXbMmDhYV78jhhRg1pmlKMxzQBQEFOY5MOvMUl0Bh1USkZkRvacfuyrIzJBglfSNJK5cUwWPN6BWUg+HZXi8AaxcU6WrXyPOAQDsrvPiYHMb2gJhhMIy2gJhHGxuw+66nqcIG/X6CgTjF6Y/UntXaY1OHqm9L1mt2iFGMooYGSGiURvkSO3pgCOJJmC3WuDX+ODQs/YPUSpL9xQ7IoCViQHjUhdHDCnA7HOGGZKGn+zMDZtkQSgswyodvugOhWXYElyEd1V1fQtkRYEsR+c8CoiOdFXXt+g7YBiTvdLqD3e4YFcQvYBvbet5AR+jXl+JYjYTxnIAommwWgUU9aTH2q0W+NvCHR6zKED369YoRs0jTWWmCBKXL1+ON954AwAQCATw7bffYtGiRXj44YcxcGA0PWHOnDkYN24c7rnnHlRWVsJms2HhwoUoKSnBxo0bcd9998FisaC8vBy33HJLXz6cbivIydD8UC7IZvVJSj9MsSOKYmViYwtvpU4avjHZRhFZORx0HZo/FokoiFjMGcmEIrLmmdCzrAQLu0UZkdCmKNE/gkabGeW5bDjQFNBsT1emCBIvueQSXHLJJQCAe++9F7NmzcKWLVtw5513Ytq0aep277//PoLBIF555RVs3LgRDz74IJ5++mnMnz8fixcvRnFxMW644QZs2bIFw4cP76uH021WSUSWQ0KrP6zezct06E8lIUpFRs0RIUo1vIBl4S0guuZersseNxcvGNZ3tW21iGjDoSymdl21H7E0EyNSLfn6ipITRG6J2rtCEOJH5yyiYNrCNQXZDjQ0BzoEsYIAFOQ4+u6g+pgpgsSYb775Btu3b8f8+fNx3XXX4dtvv8U//vEPjBo1CnPnzsX69esxefJkAMCYMWOwefNm+Hw+BINBDBo0CABQXl6OtWvXplSQaJMsCIWiqSSCIEBRFIRC+lNJiFIRU+woFRmRIs0L2KjUGfEzhjvXAbnRH7fuoN4RZYukfbVuMWlhkUiCiu+J2rsveUNcmXZJs8hMpt1Ul90qI0YSZUWJC+AjsqI75TbRGpR6Y09PSwAWUYhLv25f8TTdmOrV+pe//AU333wzAGDSpEn47//+bxQVFWH+/Pl4+eWX4fP54HQ61e0tFktcW1ZWFvbu3XvU/ysvLxOSSUbqrFYLhHa3VmL/tkoWuN361+sh4/F5Sp6iwmzUHIgvRHBcP2fSzjOfr9Rj5ufsq8r9ePOzKgDRC+yD3gDe/KwKOTmZOKWsv66+p7hdmHLaYP0H2QfM/JylkhmTT8DSd7Zqtus5x5LFAovGSI/VIpryuUsUC8pyz19rRr13S4/PwZZdDXGjUqXH5xh2bvX0Kwra8yVFoef9BhNU6A+GIrqONVGMqUDfOYjIgEUU0fkeiSwruvr9qnI//u/zPahtaMGAgiz892mDdH8v9BbTBInNzc3YuXMnTj/9dADArFmzkJ2dDQA4++yz8d5778HlcqGl5fDcPVmW4XQ6O7S1tLSo+x1JY2Nrkh9Bz7X4g2qJ60hEgcUiwOmwosUfQn19fIluMhe328XnKYlOLeuHZbXNce3jyvol5Tzz+Uo9Zn/OVq7eAW9LEN526YAuhxUrV+9AcX56piqZ/TlLJcX5Dlw4aXDciHJxvkPXOQ5HIpBlJToCc2h4RpYVhCOy7ueut4uP9fR4V67eoTmnUe97t97TGjfiJSCaKaPn3B5p7UGj3m897TfRshytbWHTHSsAWERA0Ti5FlHocb/tayxYJRF7apvx9zc3oykJ1X6TKVEQbJog8YsvvsDEiRMBRJ+kCy+8EC+//DIGDBigpo/269cPH3/8MaZPn46NGzdi2LBhcDqdsFqt2LNnD4qLi1FRUZFyhWvcuQ601Ma/ANOpOAFRDFPsKNXsrvOi0Xu44EE4LKPRG+iQIUKkhxEpt6IgQBAPjdAdujYWRf2LnW/e1YAX39+m3jSpa/Rjd60XP9G5/qIR6j1+zbUX9U5vaO1U1ROIjtTpqcQKGLdimigKkDWqm1pEc6YeG6Gk0AUoiLvZN6jQefSdE0j1GgumCRJ37dqFoqIiANF0y4ULF+KWW25BRkYGTjjhBFx22WWwWCz47LPPcMUVV0BRFNx///0AosVu5s6di0gkgvLycowePbovH0q3FfV3YuP3BwBEH3tsraKiNCpOQKnJqLvF6T4HiVJLouqKwbC+NdGIjCQrChQZHUYSFVl/wLFyzW7NmyYr1+7W9bneOTW2fXtP2SQR+zodq8cbQJ5TX0XLtgTrISZq72vZWTY0euOLtriyrH13UL2sfNRA1DX6kdFp3qieQmGpXmPBNEHidddd1+Hn8vJylJeXx223YMGCuLYxY8bg1VdfNezYjFa934fMDAne1hBkRYYoCHBlWlG9v+cLxBIZjUtVEEUlqgbJCtWULEbckBMFARZLu0Idh6pR6h1JrK7XvnbRe01jzBIFCR6szpMgJ6jOkqi9rw3Iz8TB5o7nVlGi7enCiCymVF/GyDRBYjrbXeeFzx9Sc6EVRYHPH8KeOgaJZF6pnkZBlCwlhS4oCuJS1kp0pCkRxWze1YAX3t+mvr7qGv2oqvVits70TaskQhQEiBZBrawORCuum5Er0wZvawiBdgVR7FYRrkx7j/sMhiPIc9njUgwTFV3pqlRbmH1vguvNvWk2WJHsLKZUX8aIQaIJtPrDmgvatujMXafU09uT/fVI9TQKomSJpSl1XqIgVS4EyNxWrqmCRyMlcuWaKl3fD+3nYEVkJSlzsACgyJ2FHT80xy0lUOTO0tWvTRKhKNG/Y6I/9zzwio30dE4x1DvSY9RyHUYt/9DSFtLso8XP61A92o9OelqCKMwz93VdZwwSTSAYjhx+07d79wdD5sxdJ2OkWvpmqqdRkPnFbpo0+oLIc9pM++XKYktkpOr6FsiKEhd0Vde3HG3XI2o/B8sqiercWr03N4aXFmDHvkMVqmMHrETb9RE0z4Oe1NDyUQM7jNLGsgD0noMjLddhRu1Hkju3kz6x0clUrPjMINEEEr0J+eZML6mWvpnqaRRkbp1Lh5v9pgmLLaWeVMnciMjK4WwjROOuSERBxKJvftuIIQWoqvXikw370NIWRlaGhLNOPl73Oaje70N+TkZc4KV3TqKnJVpYJZbFqQAQFKBJ52Lnna+0zHzldaQ1AvUYWOBAdX380nADC8y3hE+mXUJrIH55jUy7/pAmVT4TeguDRBOwWkS0IX7UMFExBDo2pVr6JkdPyEipdtOEUksqZW5YLSICBlwjbN7VgPWV9XBl2pCfnYFQWMb6ynoMHuDSdQ7qPdHU687p17qXlfCHD6/reIgs65uaU7GpBhl2KS7dNN0+Z047aQB++HRnh2U7RCHabjaJxk+SsXRLqnwm9BYGiSZgSZBPL1kYJKaTVEzf5OgJGSXVbppQajHyJsTba6vwyYZ98PlDcDqsOOvk43H+hME97i/TIcEfDMelWWZm6FuewKhz4M51oHKvB77WEGRFgSgIcGZaUVac2+M+gcRLyuiZmsPPmajq/T64smxxz5kZq+z7Eywjkqi9qyo21eBAkx+t/rD6Pst0SGl3w6A9RiEmIAoCJFFALLVeFAApCWWoKbUkStNk+ialI3eudpqTmW+aUOowKjh4e20V3v6sCr7WEKAAvtYQ3v6sCm+vrepxnyWFLuRnZ6hzBzPsEvKzM3RXzzXqHFglEU2+ICKyEi3EJyto8gV1j3xKFhGWdtdGghBdI1HPDXV3rgNtgTDqPX7UNLSg3uNHWyCcdp8zu+u88LZ2fM68rUHsNmGVfaOWF9la1YiWQwEiEE3hbfGHsbWqUVe/qYxBoglYJRHioQ86m2SBZIn+zDW20suIIQWYdWYpCvMcEAUBhXkOzDqzNG3vYFF6400TMpJRNyE+2bCvW+1dUT5qIBx2Ce5cBwYWZMGd64DDLul+Lxh1DjZtb9Bu36Hd3lVFbu2guKh/z4Plov5ONHoDCIdlQIlWjm30BnT1mYqafcG4ojqyDDS3xK9LeaxqTZC2nKg9HTDd1ATar7EViSiQJK6xla6YvkkUleqlw8ncjCq85UuwZICepQSMmv9t1DlINEdQ73IKw0vzseOHpsMVUxH9e/iQ/B73Wb3fh1yXPelFdlJNW4KU3TYdKZxGLddhlEQDkToHKFMag0QTKB81EFW18WVxececiNJZKpcOJ3MzKvByOqzRURklmrYXnUIiINtp0328yb5BYtiNGOHQgs9a7TpU7/ehIDsjbuF7PQGdUUV2REE7uBBNGiFpPV1Hau+KLIdV86ZJlkPfXFqjSBYB4Uj8A5YsJn3SegGDRJMQOv0jfV+SRERExjMi8Pqvkjys+aZW/VlRgIii4L9K8pL6/ySLETdi7FYR/kD8CJTdqm+GU73HHzcypUBfQOfOdWB3rTcu8CwZ4NJ1rAREEiwKmai9r+U6bTjQFJ9em6vzBk8q45xEE4iVYHbnOlDc3wl3rgMZdilh5TEiIiIyn1BYRo7TdmiR92gV0hynTV2oPh1kZ9niRsxEAcjJsuvq1yaJ8HSaP+jxBmBLUCG+K4yak8jURSCQIFU1UXtX2RIUQErU3lWuTFvcjQy7VYQrU9/rNpVxJNEEYtW0vIfmJFosAlwOa9qVYCYiIkpl9R4/cpx25DjtndrN+X0eWzy80RdEntOWlHTTkkIXoCBudG6Q7joLAmRFiVsKRE8aK+ckGseIFFYAGFqUo1lxdGhRjq5+bZIIRekYbEZ/Tt/cPgaJJmCTLNjb7Dv8wReOrvuT60rfuxdElHyxC8J6jx/uXBaCIUq2VFrvdvOuBrz4/jb1BvU+i4DdtV785Jxhuj4XykcNRF2jP26Ber11FjwtASjK4dE4BYCgAE2+YI/7NGpOIkUD+IjG0Kmoc2Jmc4v2852ovesSHFcar0fHdFMTaGkLIhxRICtQPwDDEQUtfr0veCKiqM27GrBs1U7UNfohK0Bdox/LVu3E5l36ytIT0WGptHTLyjW70dDUhrZAGMFwBG2BMBqa2rBy7W5d/Rq1nFOrPwxZViAA6h9ZVhJWU+0Ko9ZJtCWYf5mova8lmi+qZx5pothKb8y170BLt9q7KhiOIM9lhySJgABIkog8lx3BUPqkinfGkUQTqGnQXtA2UTsRUXclmuNcsamGo4lESWJU1VQjVNU2I9xupEcBICsKqmqadfdtRFGgYDiiuaRCMMHyDV1R1N+Jjd8fUH+OzUmcpDOoz860ahZByc40a2VPEQGNYEiy9DxINGrRe6PSWGNZAJ1HwM2YBdBbGCSagNZw/JHaiYi6q96jfdOJaVVEyZUq692GNMr9H6n9WGTUnESfP9yt9r6WaD1EPeskJnoVmfXVZdS6oamMQSIRURpIpblSRJTajJj/bETQYdTNs2CCaraJ2vuaEYMVRo34GSWVsgB6izmTo4mIKKlSaa4UERnPmmDJgETtXWXU/OdEy4joWV7EJok42BydlxkKy2gLhHGwuU1/RctUi5CoEz5PAEcSiYjSAu+SElF7gwud2L6vucNokUUUMFjnUhUVm2rUZb3aL4Ghd/6zEXFXS1sYkUjHeZmRiIKWNn1poRZRgKyRtmvRWdmTjBO7uRETu7kBIG2/JxkkEhGliVSZK0VExhteWoDvq5s6tCmKguGl+j4jdtd50dDUBllRoBxaoD4YjEAw4VICjd5A3FINFlFAoze+6Ex3SJKIUCR+Pp+kc5RWELSDYhOeWsNYEiytoTcAZ3G3eEw3JSIiIkozW3Y2QBQFxNajF4XoGnZbdupLC21tCyMsH1rWC4eW9dK5VAVgTHpsWFY0l9XQWzjQqGzTRGFQGsWIyLRrj29lZugb92Jxt3gMEk3AqLVkiIiIiLRU17dAFARIFhE2yQLJIkIUBFTX61tvzohKmQBQOjAbnQeLRAEoPS67x33aJBEKEPdH77xMw6rWp9AFo1EBbcICRklYAkO7PX2LuzHd1ARskvb6NDadH1JERERajKg+SalHlpVoWiiiF+9iEoINo9bHG16aj++rPfHtQ/J73KfFov14LTrWBwQMXCMwwf6J2vuSUUtgtCYYkU7U3lVcAiMeoxATGDwgG1KnlA9JFDB4YM/vjhEREWkxqvokpZY8lx0RWVFHYBQlOtKV57Lr6leSxA7pm7E/ekfnPt9ai86xkKxE23tKFITD1184fP2lt76MYUFiN9uPRYlOod44ecSQAowtc8PbGkRtQwu8rUGMLXOn9c0zBokmMGNiCZyZVnVStyAIcGZaMWNCSR8fGRERHWuOVKCB0kdWhhUWi6BmKgpCdGQty2HV1e/gQufhfoXD/ZborJq6r761W+1dkShwtUmWHvcJMJhLRZt3NWB9ZT1cmTYMKMiCK9OG9ZX1aX3zjEGiSditFthtFtgO/W236vuAIiIi0sICDQQAwXAETkenG9QOK4Ia01+6Y8bEwcjPzkCGXYJVEpFhl5CfnYEZEwfr6teIwCs3y3Z4kly7v3Oy9AXKKTR1kA7hzbN4nJNoAhWbahAIRRAIRiArCkRBgE0S07rsLhERGcOd60BdY3ygmM4FGszOiDmkNsmC1rYwLKIASRChKApa28IozNc3fjBiSAHKRw3EJxv2ocUvI8NmMfGcVwGiIEDsPDdRZzQnQDt4ZYxoXrx5Fo9Boglsq/bA4wuqP0cUBR5fMG79Ijr2sZgEERmNBRpSi3GLfBuzTkP7tD1Xpg0AsL6yHoMHuEz3fRYMR5DnssPrDyEckSFZRLiSMJpq1Lw5Mo4714Hdtd6410LJAFdfH1qfYbqpCTS3BDXbm1r0LeZKqWXzrga8+P42bN51EPsOtGDzroOHfk7ffHgiSr4RQwow68xSFOY5IAoCCvMcmHVmqeku4CnKqDS4YFhGrsuuLvAuSSJyXXYEw/oiGaOO15lgrmSi9q5w5zqQYZfgznVgYEFWu585qp5uivo70egNIByWAQUIh2U0egMo6q9vLm0q40iiCcgJblglaqdj08o1u9HoPXxjIPYBtXLtbtNevHHkk8hYRr3HRgwp4Hs1RRiVBufOdaCl1qvRri9Aqvf44Q+E4Ws3IuN0WHUf7/H9srBtr6fD+KcA4Hh3Vo/75Kh6lChqX3OKaTSUVL3fh1yXPe51W73f19eH1mcYJBKZRHW99geRWT+gjEuBYvBJBBj7HqPUYVQaXFF/J9ZX1h9e4D0EBG3iPLgAACAASURBVIIR3QGSTRKxr9MNT483gDynTVe/LW3RrKvO8/pa/NrZWF0Rex9Fv2/a4M7NSMvvG6skIhDUWq87fYoo1nv8cNglOOxSp3bOSexzF198MVyu6AdeUVERLr/8ctx3332wWCwoLy/HLbfcAlmWcc8996CyshI2mw0LFy5ESUkJNm7cGLdtKhEF7Tx1vev0EBnpSClFer5geWFMFGXUe4xSS1F/JzZ+f0D9OZZlMklnMPf51rrDAeIhEVnB51vrcP6EwTp6Nqa0Z6M3CKHTiJcoRtv14Kg6EEowBzMYivTykfQdd64DVbXeuJHEwWk8J9EUQWIgEL3jtHTpUrXtoosuwuLFi1FcXIwbbrgBW7Zswb59+xAMBvHKK69g48aNePDBB/H0009j/vz5cdsOHz68rx5OtwmCoDlRXGCt5LRS5M7Crpr41J8iHak0RjIqBYoXxkRRrLZHgHFpcDUNrYfDuXblOGsaer7uIBAtBpOZIcHbGlIrtrsy9ReDCUfkuJRIWY6268HMFRbaAbRvxni8ARSlWepxe6YIEr/77jv4/X78/Oc/Rzgcxpw5cxAMBjFo0CAAQHl5OdauXYv6+npMnjwZADBmzBhs3rwZPp9Pc9tUChKJgOjaUi+8vy3uQkDv2lJGMaqMPi+MiaK4VIWxUiU4MCoNTlGUw/P7lI7terRfWsNyKAxNxtIaYoL0qkTtXbF5V0OH7926Rj+qar2Yfc4wU74WCLCIgNZ9AYvO+ZPV+32alW7NOuWnN5giSMzIyMAvfvEL/PjHP0ZVVRWuv/56ZGdnq7/PysrC3r174fP54HQerjJksVji2mLbHk1eXiYkk+RaH2nRVbc7fYe5U0kynqcpbhdycjLx4ed7UHuwBQPys3D2aYNwSln/JBxh8s2YfAKWvrNVs13P+SgqzEbNgfgP5eP6OZP2fuD7KvWk43Nm1Hust5j5GL+q3I83P6sCAFgsIg56A3jzsyrk5GTq/sz9qnI//u/zPahtaMGAgiz8t87PcaM+EzNsEloDYc12Pf1arRZEZKVDKqtFFGCVLAa9JoQe9/v+q1+jyReb6yggElHQ5Avi/S+qMeW0wUk8xsOMel+kUr96+kw0cByR9fXb6AvClWWDK6vj3FlPSzBtrz1MESQOGTIEJSUlEAQBQ4YMgcvlgsfjUX/f0tKC7OxstLW1oaWlRW2XZRlOp7NDW2zbo2ls1JdO0Vvq6+PTD8lc3G5X0p6n4nwHrj23rEObWV8DxfkOXDhpcNyE/+J8h65jPrWsH5bVNse1jyvrl5Rzkczni3pHuj5nRr3HeoPZn7OVq3cgFI6/2ly5egeK8x097rfznOo9tc34+5ub0aRjiRGjPhPzs+1orY8PEvOz7br63Vfv05zruK/ep6vfcER7hDMckXvc764fmjRHTnf90GTY69eM/UoWQfP8ShbBkOM14znIc9oSzkk81q89EgWvpggSX3/9dWzbtg333HMP6urq4Pf7kZmZiT179qC4uBgVFRW45ZZbUFtbi48//hjTp0/Hxo0bMWzYMDidTlit1rhtjwWckUhmZ8SEf1abIzqMRTWMkUpzqo36TLRKInKdtri5g1adWVYt/lC32rsqkmBdsETt1HW5TjsONMW/9nOd9j44mr7BOYnxTBEkXnrppbj77rtx5ZVXQhAE3H///RBFEXPnzkUkEkF5eTlGjx6NkSNH4rPPPsMVV1wBRVFw//33AwDuvffeuG1TSXaWDR5fIK5iV+chb6J0YcSFcWz+UaMviDynjYEnkQFS5X2WanOqjfhMdOc60NIWht0mIxJRYLEIsFktus9B2KBgzog1pYvcTuzY1wRZUaAo0Wk+oiCk3QLqCQP7Nn2BfSrhnMR4pggSbTYbFi1aFNf+6quvdvhZFEUsWLAgbrsxY8bEbZtK/qskD2u+qY2OHB6qMKbI0XYi0q99CphVErmsBpEBUul9ZtQi6qlUbKj9yIkgCEkbOREFATJSo2L78NJ8bN/XpFbxjAWKw4fk9+2B9TJ/UHupC38gfZbAqPf4kWGXkMF1ElU6awFRMoTCMhwZ0RdlLDXekSFpzpcgou47UgoYESVHKr3PRgwpwKwzS1GY54AoCCjMc2CWjnmDMYmCTL3BpxGq9/uQmSEhIisIhiOIyAoyMyTdIyeJiqPqLJpqiC07D2q379Jup2OXO9eBtkAY9R4/ahpaUO/xoy0Q1n2DZ/OuBjyzYjNuf2IVnlmxGZt3NSTpiI1nipHEdLe7zou2YFi976YAaAuGsbsufYe4iZKJy2oQGc+o95lRS1Wk+5zq3XVedakKSRChKApa28LYo/PaI9ESGnqX1jDC7jqvZpGd3bXmLDBCxtGak9joDWCSjhs8qZRdoYVBogk0+4KaC8Q2twT65oCIjjGplAJGlKqMeJ91rhaaChdZqVJsKFG2UjCsL8UwUShovhARCIa0H2uidjp2xUbWOxdy0jOybkQhq97EdFMTaEvwYdSWIEeciLonlVLAiFKVEe+zVEphTTVWSURYlhEMywiEIgiGZYRlWXd1UyIjJZrZqnfGa/uRdatFhEUUdI+sp3oWE0cSTSCV8veJUlH7FDBPSxCFeclLWSOiKCPeZ6l+kWVmVougmcVk1RkjHqq/p9luNjarRfOGvE3vSSDDGDVSbcTIeqpnMTFIJKK0EEsBM/OCtkSpLtnvMyMvsoya65gqGpq1p7Qkau8qqyQiEIq/4LZK5kteKyl0Yfu+pg7zEi2igJIB2ouL07Er0etTz8i6UVWUewuDRBOQRAFhOf4eiGQx4303IiKi3mHURVaqzXU0IqANJJjSkqi9qwYPyMa2vZ4OIzsCgMEDs3X1a8QI5fDSfOz4oQmiEO1bwP9n792D47rru//3ue1Fu2utJK9lYSWSTOI0icaNE25JBAmkBJ6K3sYlQAvPj5JOmw6kZQopIQOh5d4ydDoUkjx/QId5YIZLWwq1f09xgPFDHbsh9eP8XDl+7CRoFUvRzbJW2vvZc/n9sdrVas85ynq/5yudr/bzmvGQ/Yz95aujc85+P7f3pzNHYIiEqkgwTP/PzEP9Cdg2kGuYkxiPahjqb39mpuhVTOQkBgBNk2G4zKIJYtSNIAiCILYKXmqhIglKcHNoJcm9r4VxnuHuZAQXLm202QB2d7Nlf3mUGU4v5NC7K+JwDDptgLosAS65CsgBzFXwatEaOziAtIuqLWtASuQqJnISA4Bp2Y4ImQTAcntiCaINOr2siiAIceGhFlqbgZZtcA4SUS2QvY4nzs667pXVoQ1rsuuw9LDGFqA+P7UMVZFgWXY9OyfLEs5PLTOty4PFTBHRsIpohw9QlzwCBhJjwIAHzSNLXsl+NTT/tMH76bcWSlUFhOZb23axEUQ71KLQ88tFWPZ6FFqkga4EQRB+ElIVLGfLMAwLsNdnooUYHSQeTM1nXffKOs8wEnLPE3jZWyVXrECWJKiKDE2RoSoyZElCvlhhWpcHqWTUw86W9fRytFkdcF7wdLxEgZSUnVAmMQAYpruikpedIK4GkcqqeFLLpi7ndPTEQ5RNJQhB4FMJIY6seMWwYNm2IzPHOs9QkgBZxgaFU1lmrjZFPKohky1vKF+UJSCZCLMtzIGxgwP49rGLjiwta4khOV384FQljan5LJZWS/XnzDAs6BUzkNnUrYKcxADQLEH9SnaCuBpIQn5jT4+myr6KVBw5lcbxMzPIFSuIRzXcfWgf3nH7MOOOCYIA+PXj6YaFZCLs6EXTjeAd4i3b3iDUYQOwTNu1h+xq17WttZK6tZ4X23LvTbsa4lENV5oUUi27ameBl2CJWyUXK2773MxOtI6mytA5qOcWigbMpufMNG3kS8HLgG8V5CQSRIDgETEXfU6PH/DKph45lcaRp9L1z7lCpf6ZHEWCYIdXP14qGYW1XHT0ogXxvWh6OK4mY7WRLEmQZama3Vr7v1BkiVmsZHrRvQzWy94q1YyOv31zJ87OuvYkBrXSxltgpnOyXbyEa7wy83qFLWMvMsEsjiaIDoRX76BX2Ywoc3r8gFc29fiZmauyEwRxdfDqxxPpvVgxrepohqY/XsO/W8W2neWPpmUzH7Z5VUd5OcUszvJipohi2cBipojZpXzD52BW2nhlea0Alknzglcpr6rIUGSpXrYqSdWgiap0rqtEmUSCCAi8sl28JORFglc2NechxBBEgQaCEBEvR4i1H0+k96IiS1Bc1EIVxpSf4XFtg6qH4O0gtb9mSJVxaaVULb1dC0LouomeeKj9RQmu2B4OsZe9VQZTMbz48ur6wExU/3cwFWNaV2TISSSIgMCzd5CHhLxI8BrIHY9qyBWcDmGMsfeGqCKS2BCNmeGDV5+RpirMa/N6L/p9LwymYpiczUJu6r1jPbyWPMroSjqbA86rd5AH+ZKxIQNl24Bp28iXjG3cFbEZvMpNb97fhxdnVtcWQ71P9+b9nfseJyeRIAKCiL2DohyMG7MGmbyO/h5/9nr3oX0behIb7QQbPMWG/IbbsHMCQ/0J2DYcAjND/fHt3porPO6F8TuG8a1jFx3XYPyOYaa9es1iZp3RvLc3iunFgqs9aCxny5Ca+vxkqWonOovphRx6uyOO52x6ga20XWTISSSIgMAr28UL0Q7GtaxBKpXA4mLWlzVr4jTHz8wgX6wgRuqmviHS6BaR9ioaYwcHkJ5zPq9BfS/yuBdGR/owdnBgTUXZQiSk+BLkUhXJtY+LNeOnqQq64yHkChVYtg1ZkhDv0qCpwTty6oblKFe17Kqd6CxICd5J8J7YDoTXzBdAnEwPIVaPDEAH4xrvuH2YnEIOiPSFLdJeRaT5qzB4RYvr8LgXJiaXcPrCIhJdISS6qr1ypy8sYnhvglHhNeKa8WOtXkklo7jikokLYlUMDzEcQkxCqoyZhvvWMCxksmXm/lSR2iaaISdxByNapocQq3eQDsYET0QqvxZpr6Jx4uwsImEVEUFGFPC4F/gF5LzcbdZMooyVnF7/bNo2VnI68xw7HvAQwyFExeO+Z8jYiNQ24UbwntgOhFcT7mZfLATBSirp3l9CB2PCD0QaUSDSXkVDtGAUj3uB1zVYzpYhN50CZZm9H+/sC+5jm86+yDbOiSB4ohsmehJhqKoMSICqyuhJhKFX2s8qi34Op0ziDka0L1dCLETroSTEgpfYEA9EKxUXCdGytDzuhVQyivRc1iGoMbw3wbRXw7Qcswsti30ERq7kPgLIa2TQdsKz3YcQi9q7prlqgeVdI/o5nJzEHYxoX66EWNDBmOAND7EhXohUKi4SIgaj0nNZvDCzglyxgpV8GYN74mwjMPbEcfrCYl1kRq9YKOsm8zWQPeYsetlbxqsKKoAlnPt2d7n2Ze7b3bUNuyG2Ex7vGtHP4eQk7mBE/HIlxIIOxoSIkKCXOIgWjDpyKo0f/ftkfTh7xijjR/8+CQBtC1z94rl5hwqpadn4xXPzTKJZFQ8FTy97q6iq7LqGGsCexKG9u1ydxKG9u5jWDWsyyi5limEteNeAqDI60of0XHZNRbiC+JpaOcu7RvRzODmJOxgeNzxBEFsDOTJ8VOFI0IsvPH5nIgWjnnzmEoym4eyWbePJZy617dDNLjmdmM3sreI28H4ze6v090QxvZh3tQcNrz5J1v5JNwdxMzux/fBQERapbcINchJ3MLxkswmC4As5MvxU4Wh0Cz9EV/LzA6++O5Z+PF5D73kRi6iQsLG6VFqzB41cweP35WEndi68vhtEaptohvLeAYBXX4DoqkoE0anQs8vvGoguJBBk6L4Fl348br2DnJjPFB0/rg1gPoDPmEDtkwRn6LvBSfDCOh1IRJNRKJuudhbohicIMeH17IpUwsrrGoguJBBkeP3OjpxKO9omWHrxeMKjH0+WJUdPYs3OAi9lz9WGGYkb7WyjNXhA6qZEjVQyiqm5LLINKsKJqIYhRhVhkaFMYgAo6k4HcTN7q9AcO4IQEx7Pbq0UcH65CMteL2GdmAzm7DJe7y+aacgPHr+zmhBMJltGpWIhk60KwRw5lW57zRoTk0t44ocT+Mw3n8ETP5zw5VnYP5CA0uS8KbKE/QPtHzRDqoxmf1CWqnYWmvf5SvZWEWlAfUhTrspO7FwG98SxnC3DMCzABgzDwnK2qk7cqZCTGADcolib2VuFDkMEISY8nl3RSgF5vb9GR/pw+K796O+JQpYk9PdEcfiu/YHNqIoEj9/Zk89cgmnZ9e9D264qez75zKW21wSqDuK3jl3ExOQVzFzOY2LyytpnNkdx/I5h9HVH0BVREdJkdEVU9HVHMH7HcNtr9iRCDgfLsqt2FkwPgRov+04k1R2+Kjuxc5leyCGZCFez/lI1+59MhDG9kNvurW0bVG66gxFNOpwgiCo8nl3Rys95qsKJpJYpEjx+Z/lixbU/LM84mP3oyTQy2fXyR8OoZimPnkwzi1S8994DPn/vemX22DJ+1I8H8Lq2hHgsZoqIhlVEw2qTPZjfkVsBOYk7HDoMEUQVHtL8PPH72RWxF09kVbhOxe/fGS9Hxm1Ew2b2q8HvZ3c5W4aqSLAsGzaq7ossS1jOBq/HTzSWs2VXJdZOu7bN16DR3imI+B3Jm0A4iZVKBY888ghmZmag6zr+5E/+BHv37sUDDzyA4eFhAMB73vMe/Pqv/zq++tWv4vjx41BVFY888ggOHjyIqakpPPzww5AkCddffz0+9alPQZapkhYQS6iCIHhB0vziD/UlOhNZkmC69F7IpCzCjOIhiMPakygSJd10VWItMWpCiAZllfl9R4oWoG4kEE7ij370IySTSXzpS1/C8vIyfud3fgcf/OAH8Qd/8Af4wAc+UP97586dwy9+8Qt8//vfx+zsLB588EH80z/9E77whS/gwx/+MF7/+tfj0UcfxU9/+lO89a1v3cafKBjQrDWCqEKz8aj8nBATL1+Q1Y8ZTMXx4ssrjuxcEEUqehIhzCwW6p9tVPsGe3rZehJFm7/IA8tD/MHLTuxceHxHih6gDoST+Pa3vx1ve9vb6p8VRcHExAQmJyfx05/+FENDQ3jkkUdw+vRpjI2NQZIkvOpVr4Jpmrhy5QrOnTuH173udQCAN73pTXjqqafISQQdjAmihmj9eLyg8nNCNHbFQljN6bDsqniNJFWziIkYm4N08/5evPjyitM+0su0Lg9ikRAUuei4BrEo2zWg7BE/4UBCTPz+jhT9HB4IJzEWiwEAcrkc/vRP/xQf/vCHoes63vnOd2J0dBSPP/44vva1ryGRSCCZTG74d9lsFrZtQ1oLN9Zsr0RPTxdUNfgSx6lU+7LZyzkdmotEdiavM60rGv/nwgJ+8ouXMLeUx96+GH7tddfi1hv2+Pr/0UnXU0QG+3dh9vK6QlntuXjV7jj97gSBfk/i4cfvbHxsP7735EU0f1uPj+1nWn9xpVx1QPM6TMuGLEvYFQvh8kqZed9+f+dYAPb0dmE1r6NiWtAUGbtiIdjg91x0yrqyJLlmDWVJCtxed9K6Iu2VheZzeO2/RTmHB8JJBIDZ2Vl88IMfxO/93u/hN37jN7C6uopdu3YBAN761rfiM5/5DO655x7k8+tN5fl8HolEYkP/YT6fr/+7zVheLrzi3wkCLI3/PfGQaxNuf0+0Y0QgajLnubXhqDOLOVyYuoL33nvAtygOiWoEn9fesBv/NLcKoPqSrg27fs0Nu+l3JwD0jImHX7+zNx8cQD5fxvEzM8gXK4hFNdx9aB/efHCAaf2LL12pZyhhV0ssV3M6Lry0zLRuc5vHS3Or+MaPJrDCMGalJx7CSq68lkm0Ydk2DNNCMhbi9lx0yrohTXbtPwxpcuD2upPWFWmvLDSewxvPHkE7h3s5rIFwEi9fvowPfOADePTRR3H77bcDAO6//3588pOfxMGDB3Hq1CncfPPNuPXWW/GlL30J999/P+bm5mBZFnp7e3HTTTfh6aefxutf/3r8/Oc/xxve8IZt/omCAQlV8JM5J8SC5zgFXogkOiXSXgnxeMftw3jH7cO+rlkoGRtEW2wbMG0bhRLbaA0e5WWDe+J49vnL9c+177HBDvou5wX1JBKNHDmVxvEzM8gVK4ivBaRY3j2in8MD4SQ+8cQTWF1dxWOPPYbHHnsMAPDwww/j85//PDRNw+7du/GZz3wG8Xgcr3nNa/Cud70LlmXh0UcfBQB87GMfwyc/+Un87d/+Lfbv37+hv1EEZAmOQbk1OwskVMFX5pwQC5HGKYgkOiXSXgmihr4W0W+m4mFvFR79z9MLOfQkwsiuVcSoioxEVOvoId9+oVfcf99edmLncuRUGkeeStc/5wqV+ud2HUURA9SNBMJJ/MQnPoFPfOITDvt3vvMdh+3BBx/Egw8+uME2MjKCb33rW9z2xxsvITF/BcYoKkYQonDi7CxKZcNxKAxis7vojflEZ6LKEkyX2YOs4x9SySjSc9l6i4OqyIhHNQzvZeifzBRdxzSwCm/JMmC5+EJyB43AIIgax8/MeNpZsokiBaibCYSTSPCBIvxVmfPJ2VWnPYAy5yJCZYZ8mJrPbhjmbBhWdegz42w4Hr8vUo4lRKT23SArG58p1u+GwT1x/OeFhbrzpVcslHSDqbwspMqYcWmb6ImzqZvKkGC5BJBpyjTRieSKFViW7VARzhfZStBFhpzEACDBPc/HGsujCD8wfscQvn3soiMjM377EPPaIg9I9QMKQvDDq+RNN9of8Mzr95VKRl0FslLJSNtriggFTPjB49qO3zGE//HDcyiUjHomsSuiMn83/OK5eUd2zrKq9vazER6nAcagEfXjEcQ6YU1BrrLuENb6lKORznWVOvcnDxC8ZhVRhL96+P39ew/43pcp+oBUP6AgBD/cRtdU7e2P7eFVwip6Y74fiBgwEcWpnZhcwtePnkeuUIFl23hpPocLlzK4f/xGpv2m57IoV8y6nyUBKFdMpOeyTOvOLrkrp3vZW0E3THRFVGTXroEsSUh0acx9c1vT6kIQYtAdCyFXcGYNuxlnsooMOYk7GIrwV+ExQJwcJPGCECJlfof6E7BtOPqahvrbL4XjVcJKAlnivQ9Ecmq/97PnsZLT659N28ZKTsf3fvY8Ru9vf6/Hz8xAliRHuSlr/5Hp4WF52VshpMpYzet15820bayuiWAQBOEPmiojFJJR1teDL+GQzBScFR1yEncwFOHnh2gOEg9SySim5rKOzNQQg0BDDb+zHM3ZCFmSfMlG8GLs4ADml4uIhlWHvV14lLDW4BGIEQnR3gciObUvX3bPwHnZWyXn0WfE2n8kSdUyNTd7u8wuFRzZPcsGZq+IMe+ZIESgYljQdWtDcbeuW6j48B0pKtSfvIMZHenD4bv2o78nClmS0N8TxWGGgb7EOqmkewS3k7K0g3viWM6WYRgWYK9npliFH2pZjvnlIix7PcsxMbnU9prf+9nz1cHZayet2uDs7/3seaa98oLHs8ujhJWoItr7QCSnlldJZDyqudpjHvZWkTz6B73srZB1KYEDgGy+cwU1CMJvVnI6bMDxZyWvb/rvdjKUSdzhdHqEnxeUpa3O7komwo6SSNbZXTyyHLNL7odiL3sQ8PvZ5VHCSlTh+T7g0TsoUiuCLEv14E6znYW7D+3bMBOt0c6CqkjQDed+VaX9/fLSLeA1o5kgRKSoG+72cudmEslJJAKDKEIKAL8BqSJdg8VMtRyyuSSSNRvBI8the6j1edl3IjxKWIkqvPoyefUOihTk6k2EcHml7GpnodZ3ePzMDPLFCmJRDXcf2sfUjwgAXVEVetaZeWDNUPKAhGsIYh1ZkiC5jYTp4KAJOYlEIBBJSKGG3wNSRbsGvLIRPNaNRTRka71GDd8BXiVnOxESmOGLSAJZIt0LfbuiWM7qG4RfFFlCXze7aMs7bh9mdgqb6U92VUVmGlqAZRnYwyAyoygSTNN5eFUYspMEQWykK6piRZAAz1ZBTiIRCEQSUuCFaNeAVzaCx7rX9MfxXHrZaWfsnxQNKj+vwiNjz2NNnr2DotwLumEi0aX5Pv4B4FW5YUOVZafiA0PVQkRTULSMDRk+WaraCYLwhwODSZybvOKYnXr9YPd2b23bICeRCAQiCSnwQrRrwCsbwWPduSsFyDIc0f05UgfsOHhk7HlVAYjUO8iLkKqgUDKgyBKUNfGXQslAfy+b7h6v35luWIhG1A1KyvEuzbVPsVUGU3G8MLOywdGUJIlZJIzgo0ZLiMngnjieff7yBpG3imH5IsYnyvitZshJJAIBHYbEvAa8shF+r5srViBDAiS7HiGUITHL3RPiwSNjz6sKQKTeQX54OFeM/cS8fmchVUauUKmXx5q2jVyhgr0M5aa7kxFcuJTZYDMtG7u7g/vdQBCiwUOMb2JyCd86dhG5YgWmaWNGkZCey+K99x4QwlEkJ5G4aniU6NBhiK4BT8KaglxlzSFcixybto1ohF6BnQaPjD2vKoDRkT6k57I4fmYGuWIF8TVxlSAfLvyOmuuG5XpwY8nMAdXf2eVM0VFaJjOmkJZWyxv6J4GqQ7e06hTfaZWzL7iP/zn7YvtjgQiC2AiP9/jRk2lkstVnX5IkGIaFTLaMoyfTgX6P16ATEnFV8CrREfEw5DciiUmIRncshJzLrLHuGJtCIsEXHmU6PDL2vKoAaj9/Sa9KsJd0EyfOzmJ4b4L5Ohw5lXa8b1lFXBq/HzRV9uX7IZWMYvlSBmXdhGXbME0bIVXG8N4E016zBR350rrkvQ0gXzKQLbTvzAHA0qr7gdLL3gr5UsV1yiJVQrAjwT1XTdWmnUdIlTGTXX/+aw5dT7z9c8L0Yv6q7EGDnETiquBVosPzMCQSoohJiIamyuiOh9bFL+Sq+AUNkg8uvMp0eGTseVUBNEahAfgWhT5yKr1hRmCuUKl/ZnEUeXw/aKqMTG5dcdC0bWRy+oa+oXa44pHZ87K3ilcVLEt1rCRJsFwWTldA/wAAIABJREFUYM16EtVr6/bLkejadiASDNNyCER1coMqOYnEVbGYKSKTKzua8lm/rHgdhogqIs1f5EEqGYVlA93xMDRVRsWw1uzU0xNUeJXp8MjY86oC4BWFPn5mBpZtw7IaenRlCcfPzDA5iTzKtXiVWoo0IzAWUbHqUgkRo3J5Ztyc783sxM5lPlNwPP+WDdcqkVYZTMUxObvqtAsiOkVvmB2O385BxTCx2hDVtWwbqzkdiSjbrTS9mHc9tIiSkg8yos1f5AHPfs9Od8B5wbNMh2/GPviHy9W8vmHung3ANG1k82zli6lkFBcvZRzjKg5ck2x7zaxHSWXWxWnaqZQq5lXZidbhkfklxKRQNFzLjAsMZd3jdwzh28cuIlusilmpioxEVMP47UPtb3QLISdxB8PDOVjJuT8sK4yHC9OyXQ8tpkJvalZEm7/Ig8ZMTyavo7/Hv9l4vBxwcj7Fgdd9MJiK48WXVxzBM9YotCxJMF2cWdaqKk2VsVILIkqAZdlY8aE0lAey5J41lIO3Vc+ZkH7MiiQIoopX9pglYDA60oc7Dw7g+JkZ5EsGIiEFdwr0XU5O4g6Gh3NQNkwoiuQ4tOiMEU1NkVGGcw0/DhedftgWbf4iL2rZo1QqgcXFrC9r8uzRFSn7y+MZG0zF8eLMCiy74V0T0NlwvO6Dm/f34sWXV5z2kd621wSArqiKTFZ3sWtM656fWoZUm0e6drCS5ao9aIRDCopl53dOmAbUE0RHsisWwmped5xvE7H234sTk0s4fWERia4QendFUDEsnL6wKIzeBjmJOxgezkE8qiFXqEBWNoacY4yHi66oiqJuOB7OrgjbuqIdtnkg4vxFUVjMFFEqG8g2yPMnohqzA85bIMpPZ47XM1Z3kBqjuBK7g8QDXoGY6YUcendFfJ3bBQD9yS6s5nSHQEM/wyw/oFrGaltrypBrspG2BaYyVlWRYJjOUL6qsKU9KTtHEEQjdx/ahyNPpR3n27sP7Wt7TdEruchJ3MGkklFMzWUdB9ghBunwuw/tw49OTDqcOZaHCACG+hOwbTgOQ0P9bFkD0R9QPxBx/qIo2d+QqmAmu94jZxgWlrNlJBNhpnV5OJ+8nDlez9j0Qg59uyL1Xg5FlpDwwUHiAa9AzGKmiGhYRTSsNtlZqwCqvTFOM1t5P48y1lftjuGleefv/FW7Y+0vimop7NXYtxMPAc5OFl0kCN+piXYdPzODfLGCmA+jgUSv5CIncQczuCeOZ5+/XP9cO8DeyeAcDO9NIKQpKK4NIAaAkKYwz6waOziA+eWi4zDE6sgsZooolg2H8ynKA+oHjTMoG198QXS6ANGyv3a1n7bhYKnIHie6q4CH88nLmeP1JbiYKSISVhEJqxsUaf14dv0OQvAKxPByPnkNqO+KqljxuYz15cvuQkVe9lbx+kmD5yKSuApBbBXvuH2YeV5sI6JXcgWwRZvwi+mFHJKJMFRVBiRAVWUkE2GmSPzRk2kUy+sOog2gWDZw9GSaaa+jI3247YYUsgUdc0t5ZAs6brshxewUhFQZmWwZhmEB9vpojZDaOSHYxpr4vX0xJLpCOH1hEROTbBLyvNjMmWFhYnIJT/xwAn/+d/8bT/xwwpeffz5T3OAgAlURpgUfMj2WbcMwLVRMa212k810KuTlzKWSUZTKBhYzRcwu5etZUNYvwVTSvfTRjwH13zp2EROTVzBzOY+JyStrn9u/H0ZH+nD4rv3o74lCliT090Rx+K79zO8vLyfTD+czGlaRSkYx0Bdr+Mx2bQ8MJhFdG8tQu1WjERUHBrvbXtOt1HQzO0EQRFDg9Q7fKiiTuINZzBQdcr4S2A6FL8ysOs6ptl21s9DoyCS6QgDgU3OvBMOyqkIKa8gyfKnTqWUjlnM6euKhwJZEilZyy8OZacxOaqrsW3ayUDRc7XkGyWwAyOT16kiYtWfNBgDbZlIR5hXR5FGxAFS/RL9x9LxjnMLhu/YzrctrJiuPsRq85i/yynzW7gVNlSFJEmzbhmFYgRQbIgiCaMbvKhNeyupbRctO4vnz5/Ef//EfUBQFd955J1796lfz3BfhAyFVwaWVXFUdcC2LpusmU8lac9bkleytwsuRmc8UNjiIQFV5b4FhOCrAz+ng0YsnWk08j15aXvdXrQSyVXurFIqG632bL7XvJI4dHKjPa2q8rqyOwfRCDl0R1eHMsfYOpueyyBUrsNeiUrZtI1esID2XZet15DSTlVcfrUjO5/RCDj2JsGMmWBD7SAmCIBrh1erCQ1l9q2jJSfz617+O7373u3jLW94Cy7LwwAMP4IEHHsDhw4d5749gIF/SNzhvtg2Yto180dkzst3wcmRyHgOXswW2a3Di7CwyuTJyDQfjeJfG5HRMTC5tOMTPLxcxNZfF7997gOkFJVpNPI/MFK/7i1dfU6Hsft8WGJxEwLkvPwr2puazyBXWnDkbsGEjV6i4io1cDcfPzECWJMiKVM9K1ewsPSM8ZrLWSlhzDc9uei6L9zI+uzzh4XwuZorr91RDFjyIASkSgyEIohHRqq62gpacxO9973v453/+Z8Tj1ZKRD37wg3jPe95DTmLAWc7qkJoGBstS1R40UskoLl7KOLIRB65JMq3LK/N5cTqD1aah0as5HRennTPNWuXoySksrZbqGQ7DsKBXTBw9NRVIUQ1eTC/kEI2oDgecJRshmqPcnEV8JXsr8PoCLJQM92AUo0Ob8yjZZS3l5TGT9ejJNJZWSvXroFcslHWTuYRVNEKqjEsN7zDJAPSKiZ54aLu35kBVZNeMv6vqK0EQOx7Rqq62gpacxGQyCVVd/6vRaBSxGJv8NMEf3bDQ7AtZdtUeNDRVxkpu3Xm1bBsrOZ3p4AasSbK7hItlxnCxVy9ageEAOzWfdc1wTM2xlSeMjvTh6efm8cz5BVRMC5oi47U37gns4XVqPotiyYAiS1DWumqLJQNTDJkp0Rzl2ow5V3ubTM1nXXvxphifBd2wXLfK+p6pzWRtxo+ZrIWy4VCkZZnJ+svZrKuA0S9n2UuLjpxK4/iZGeSKFcR9kGSvwaM8Nl8yNgjK2AAs00a+5P6+3E68bnvKJBJEZyJaMHkraMlJ3L9/P971rndhfHwcqqriySefRDwex1e/+lUAwIc+9CGumyTaQ6Q5UOenliHJcAjMnJ9aZlq3JxHC5ZWyq50Fy0NlkkWSvOJx2GbtbztyKo1TE3P1gIFuWDg1MYf+3i5fpZ79omJYjmshAagYzuxPq4jmKGuq7DrUmyVoUjEs1148lusKePutrGftuw/tw7/8/JeOSgjWmazJWBiLTQcB27aRZMh28epNPXIqjSNPpeufc4VK/TPLs8ur98Y7Es/WA84Dt+drMztBEDsb4YLJW0BLTuK+ffuwb98+6LoOXddx55138t4X4QO8Si15sJrXXYU6sgxqjjzZFQshky1XD7Brl1OWgESMLcvBgyMn064Z5SMn08xOIp9sRMW1d67AkI04ciqNk/81V19XNyyc/K/gOso8sG24ZnlYZ61pioySz+WbADB/peB6385fKTCtmy/prusGsVf7+JkZTzvLfXvi7Kzr/FhmISePsRRedoIgiKDAS9BLZFpyEjfLFP7xH/+xb5shOhjPYcFsh4srHv2XXvZW2dvbhSurGzOUll21t4tXdtLL3iq8Iua8shFe+ypX2s94/ejEpKvj+aMTk4F0Enlkpkpldye7pLOVAioeM0dZe7uefm7e037/+E1tr7voUlmwmX07yRUrqJjWBkdektj7Mqfms7icKa5XF1QslMoGJMZaS6/3Net7nCAIYivgIeglMsxzEhcWFvzYB9HhuPUNbmZvFV4lt5Mvu8+FnJxtf16k148a1PPVibOzrv2SrNkIHtdBtIHcPK5BUXd3sotltnLTjEfAZTnL5nTx+p2VPa6Dl31bsZ2/8zURWSaWa1UQDVg2sJxlVPsV7B1GEATRCK8ecFHZMTJelmXh0Ucfxbve9S68733vw9TU1HZvibgKRDtc8Dpwi8QvzrsHiLzsBEFcHV7iP6xVANSPRxAEsZFaD3iuUAHs9R7wI6fS27yz7WPHOIk/+clPoOs6vvvd7+IjH/kIvvjFL273lgiCIAiCIAiCCDjHz8zAMC3oxvofw7Q8e8M7AeZy06Bw+vRpvPGNbwQA3HLLLZiYmNj07/f0dEFVla3YGhOpVEKYdUXaq2jrirRX0dYVaa+81hVpr6KtK9JeRVtXpL3yWlekvYq2rkh7FW3dIO51JecuaraS033bL6+fmxfMTmJQGtJzuRzi8Xj9s6IoMAxjw3zHRpaX2RTytorFRfY5W1u1rkh7FW1dkfYq2roi7ZXXuiLtVbR1RdqraOuKtFde64q0V9HWFWmvoq0bxL1uJh7ox35TqQS3n5sVL+d103LT+Xl3dblGfvu3f7u9HflMPB5HPp+vf7Ysy9NBJAiCIAiCIAiCAOCtCBaMXNi2sKmT+MADD9T/+xvf+Ibr33n/+9/v64ba5dZbb8XPf/5zAMCzzz6LAwcObPOOCIIgCIIgCIIIOrLsPgLIy94JbOokNpaS/uu//iv3zbDw1re+FaFQCO9+97vxhS98AR//+Me3e0vEDsbrlcHyKglp7o+jl71VomH33lsvO0EQBEEQRCcx0BeFBDj+DPRFt3Vf28mm9ZiNg3WD0nvohSzL+PSnP73d2yA6hFBIRll3ysWHQ+07XjwcTwC49UAKT/3XnKudBVmWXOdNdlLU7abhHjyXXna1E8FEkSWYLvetEsD7NhpWXMfqsAZ4JMl9vJAUvEtAEASxJdz3luvx9aPnkStUYNk2ZElCvEvDfW+5fru3tm20nKKQ6NtDOHg5HQQQUtwPaZraftZPVWQ0n1NlqWpn4XKm5Dj8SRJweYVtcPb1+7pd171+sJtpXR6EPbKxXvZWWc27D5L3srdKl4cT4GXfTrx8K1afK+TxLHnZWyUR01ztu2KhttfkdQ28AjmsAZ59u7uuyt4qXscEOj4QBBF0Rkf6cM9tg+iOhxBSZXTHQ7jntkGMjvRt99a2jU0zic8//zzuuece2LaNhYUF3HPPPQCqWUVZlvGTn/xkSzZJtIckSa4ZYInh5CJLcEgE1+wsyDJgucxxlgM6ybNiug+drngMv26FnkQYhZKxwYm37aqdhfTcKmA3BQdsID27yrTu+B1DyBwrI1uswDAtqIqMRFTD+O1DTOvyYHhvAi/OrMKybdioXgtZkjC8l02O+uXL7irJLy+xqScrsgzAmUFSGAMGPNA0BWXduVdNY3NoX3vjHpysZcAl1MUDXnvjHqZ1ZUlyvMdkic2RSfVEMX+l6LDv6WFzuiqGhWQ8hGxDZDvRpTG9ZwCKmBMEQTQzMbmEE2dnUdJN2ABKuokTZ2cxvDfRsY7ipk7ij3/8Y5RKJaysrKC/v79uv3z5Mr7yla9w3xzBhiwDlvPsxuTQXT+YxIVLGaf9mmT7i6Kalbp4aWWDiJS0Zg8iPESwYhENilIt4aw7MrKEWNQ989Eqhmm77ssw2UrIR0f6cOfBARw/M4N80UIkpODOgwOBfJmO3zFcPxTbtg1JkhDr0jB+xzDTup6S2W6RlKugbJiOskhFlqBXXB7obSbVHcH0Yt7VzsL94zdhOVvG/51ahmVX31u/MtSD+8dvYlrXsm3YTUET23YPfrWK5uG8qwpb9GwxU0R3PIzueLjJzlYFMDrSh9GRXjxzfgGWaUORJYyO9DI/u1TGShCEqBw9mUYmW65/NgwLmWwZR0+mA3mu2Qo2DUv/4Ac/wO/+7u/i/vvvx9TUFPbt24d/+7d/wwc+8IGt2h/BAgdPZnfS/eC3m/FAOH7HMFI9UXRFVIQ0GV0RFameKPMhnhdeDw6LA64bJvp2RRAJq9BUGZGwir5dEegVtqwBL8WuicklnL6wiERXCHv7Ykh0hXD6wiImJpeY1uVFRFMQDikIrf1vhDHTxZOwqsCy7A3N85ZlI8SwZ6+MNGumOhZRocrV7Fw1QwuosoRYhG0E0cTkEvIlA9f0J3DdYDeu6U8gXzKY7y9ZkqAoUtVxWcsgKorE9Owurbo7bV72Vkkl3QUTUh7v4VY5ciqNU+fmoBsWbBvQDQunzs3hyKk007qKR+mHl50gCCIouAU7N7N3Apt+i//gBz/Aj3/8YywsLOArX/kKvvGNb2B+fh5/93d/hze+8Y1btUeiTTYbDNou56eWobpku85POcU7robRkT68994DOHF2FouZElLJCMYCmpUCNvG/GRzwVDKK+eUiImG1yc52IIxoimt5WoRBZAcATpyd9bSz/N54iMGcODuLSFitO+C168G6V16Zk+64hmyx4rR79NO1wvWD3bh4KeMoXWTtIdUNC73dEeQayo7jUQ26wZZN5XV/aapcLTltyvKF1PafB7dy283srTJ2cAD/9L9/6Wpn4X+dmnKU91sW8L/+YwrvuH247XUVWYLzrmUTBeLV4kAQBNGMZdnr1SZSNajYyWwa3ovFYtizZw9GR0dx9uxZXHfddfiXf/kXchA7mFyxAlmSoCoyNEVeE1uRkHc50F4t6bksXphZwczlHF6YWUF6LuvDjvmgyBLUtexD9UVSLS1jOQx5HfxYD4RdUdWxL0WW0BVhK2NdzDh7sKp2tuzJR999CDcN99QPgbJUdRA/+u5Dba+5mCmiWDawmCni0nyu4TPbXr0yeywZPwComLariBFLtenYwQGE17KomiojHFIQ1hTm+yuVjCIaVpFKRjHQF2v4zBbc4HV/DfUn0JMIQ1VlQAJUVUZPIoxr++Ntr+kl7MYq+DY60ofDd+1Hf08UsiShvyeKw3ftZw6eFT2cVzcl1atBU+T17Le0ngVnEfTyCmaxBrkIgiAa6UmEYVp2PfBr24Bp2czVNiKzaSZRbigR6enpwcMPP8x9Q8RW0P7BJR7VkCs4HULWvrkjp9I48lS6/jlXqNQ/s0S2eTGYiuHFl53CL4OpWNtr1g5+fmdTk7EQljIlyGtZr9rhLcmQlQLWM59OO5tzAIDJIXQjpMqYWes1kCSp3mvQE29f0RIAhvvjePHlVUdmfZjB4QCAQtFwZE8sGyiU2IIxzQkZPwYb8cp28bq/xg4OuGbsWfbbkwjh8krZ1c5KtX8wmBUVzXRFVRR1Y/15kKrPA0tAytOhZczSEgRBNMJLF0JkNg3vNUZBIxH2gx+xtXiNTmARU7j70D5Ytg3DtFAxLRimBcu2cfehfW2vCQDHz8y4rnv8zAzTurz68W7e3+d64r55P9thbnSkDw/81ig++f+8Bg/81qhPh0M+uvS8Mp984HMNxu8YRm9TH2nvrghzL23JI2VYYjgYnzg7i3LFRFk3UTEslHUT5YrpWdbZKqMjfbjthhSyBR1zS3lkCzpuuyHFfO+OHRxwzf6y3l+jI30YTMUwezmPl+azmL2cx2AqxrTfvl1R18xvX3cwhzDzGlUx1J+oPw8hVak/D0MMQROvEv6Aj24mCEIwdMNEPKrVfR9JkqqtE4y6ECLT0ggMAJifn98wAkOSJPz0pz/lv0OibbqiKipZ57w2lqjI8N4E4lEN2QaVyHhUYx4lsJrXYTaobdoATNNGNs+WOen1iPD3Mkb4pxdy9T4s07ShKNXrML2QY1qXB5l8GTbW+3pq2cRMjm2W3+hIH55+bh7PnF9AxbSgKTJee+OeQGY9dMNETyKMbLEC07Lr4zpYX/68emm91FFZVFMvTmew2vA7t2wbqzkdF6dX2l4T2ChglOiqPlenLyz6Ihuurzm1lm1DNiXmGYlAtWrhmfMLANZVSZ85v4D+3q62qxYy+fKGMR0AAAlYYXzGeLFvd8xVjGHf7vYrIYD1LG20qfc3mIEjgiCIdUKqgkLJgCJLUNYCy4WSgf7ezhXeesURGIS4HBhM+i5UceLsrKskO6uYhCxJMF2K31gj27z6WRYz1YNQ82GItV+qNqdnMVNEKhn1xeEoFI26UmYNy7KZSxePnErj6efm646LYVp4+rl5psN2Db+vQyoZxVStx9VutLNXSNR6aXPFClbyZQzuiTP/zjRVhuU2e5DBSSoUDdfy0gJjPzEvgZmjJ9PIFSv1Wa+2bSNXrDDLkXtVJxw/M9P2fVsoGa5CMHnGZ4wXr7upH7P/PukYsfK6m/o3+VevTGPJfCavo7/Hn3cYQRAEf6qiNc3lpp1ctrCpk7hvH1sJIbG91KK6zQ4dS1SXl5hEV1TFikvWs4uxFnw5q7uqsS67/H9dDTz6pSYmlzb0ds0vF+ufWQ5ZFdM9W8Y6kPvJX1zaMGvRBmCZNp585hKTk8jjOgzuiePZ5y8DWO9JXM6WcSdjhoNXL+1QfwIvzKw4DvFDDBl7o9mLWcNknOlYKwNtVjdlfSek53Pr1QVr39OmaWNqni1bn/NwilnEt7zKgFnKg3kyvZBDoktzBBD9qISo9VCmUgksLgZXfIwgCKKRTF5fDyLXDow2kGGsaBMZtkFWRKDhIYRSy8hkGw6EiajGdHgFqlnPC5cyyDUcWuJdGg4wyvMDNUnj6n/bANvU7DXGDg7gW8cuOspNWRxwXhkZZW2AXWMwTJLYZOkBIOeRJfE6hLfKibOzrk4Hy3WYXsghmQjXf1+qKvtSHswjKwUAN+/vxYsvr1TFhrCuFnnzSG/ba6qyDN3FUWS9D0KqjKmVYj2TplcslHSDWRTI8AhisAY34lENq3ndETja1dX+fnmUB9f4+tHnHCXd94/fxLTm1HzWtazqJUYHnCAIQlQqhgVZliA3aRhUjGAG+7YCchI7Bn/S5Y0ZGQC+ZWRqWc+kj1lPAIiGFeRLxgabZVftrEhN/8E6TYdXllaRJUe1hG2zOwfewyLZlp2az2JppVTPcOmVqsgKyzgBXuXBPLJSwFrP6y7n7EEWpzakKdBdHCzWcR1LqyXXUkvWQfKqKkN3ycSpjH2JNw714OR/zdU/1/qfbxxqfw6nLEuuGVlWgayvH31uw14rhlX/zOIoejnaegcfhgiC6Gy82jlYZuiKDjmJOxgeZXvTCzloqoxCyahH4bsiKnNGZnSkD+m5LI6fmUGuWEE8quHuQ/uYe1nKuvthqMwoWMJjOHsqGUV6LutwDFhFgQpNTvIr2VtFbfi5m+0srOZ1x4HbtGys5p0CRK3Ca5wCr5EwPAIGIU2GUpYcJawhje33dcWjdNvL3iqO8SKSP+NFKoaF7njIUWrJkqFUFQkVl8eJRUkaQF1gx83O4iR6HYY0Hw5DR06lcfzMDPIlA7GIirsP7QvkGCOCIIhGhvoTgA1HpRzLDF3R6VzJng5gs/LFdnl+eqXuXNSOP4WSged9UEh86uxsvYenpJt46uwsJiaXmNYtG6brIHmdZSo5+BziB/fEkcmWq2V2Nuqz/Ab3sL2gTI+may97q+wf2AW56Q0iy8D+V+1iWpdHfxevcR1eo19YR8KEVNn1Xgip7TsdmipXnUJVrv+pfmZzDHiVWo7fMYxYkxx5LKoxjxdZzFT7tAf3xHFtfwKDe+LojoeZnl2vH5W12tSzn9jD3ipD/QkkE+FqQEeqBnaSiTDTqApgvUc3V6gA9nqP7pFT6bbXbH7HvJKdIAiiHcYODriOiepkdWbKJO5geDgyXmV0rOV1R09OrZWtVbMGhmFBr5g4emqKKZsYVhXkKhWHsmcownbr88hMTS/k6mMaGqNYrFlaRZJguDiECvOMwCF8+1jZsd/x24eY1uUxF42X6mItQ3L8zAzyxQpiaxlw9syJ5K6yxvA74xUllTzE31iViQEgoimohCyYlg1FlhBhLI0F+Dy7qizBdBHIUhnLTTXFPVuveczAbZXGURXNdhZ49OiGNQXFsjNAFPbhXiAIgqiRnssitzbeDTZgw0auUEF6Lst0VqiptS/ndPTEQ0IpPlMsbgeTSroPcmY5DFkeJ3WbMSs1NZ+FadrVw6bdoGQ4x6aO1x13L/vrjrGVA/LITC1mioiEVaSSUQz0xZBKRhEJq8x9c8lE+KrsrTI60offv/cARkd6sW93HKMjvWuf2V5+Xn1crP1dNfxWsx7em8B1+7rxqt0xXLevm7k8GFibu+cCy9w9XtlU79JFtq+XWkl3KhnFNXvi9eeBpRIC4HMdBlNxyJIEVZGhKTJURYYsScxVAK+9cc9V2VtldKQPh+/aj/6eKGRJQn9PFIfv2s/87PLo0eURNCIIgmjm+JmZanBPkaGpa+9xWfIMfrVCre1rfrkI27brbV+sVXJbBWUSdzBjBwfw7WMXHZkDlsPQrlgImVx5g1CFLAOJGJuSoVc/EKuSoaYqiEZUFBt6KKMRFZrKduvzyEzxUo5NdGnIFSsbyjUjIaU++Nwf/Duxvaqvy3XQ96v6utpes7E/V1Nl38aLcBtbYliQJQlyU08bq7BI82/Jj98ar0M8LyEnHqrP1ay6813LmlWv9R36rW4KrI+q8JN4VMNqTodlN2RUJQm7GJRuOeljIaTJ0F1601l7dAmCEBMeQS5eqvVbBTmJO5zSWn21ZdswTZs5un/jUA+ealDbA6pKhizKgEBV4EF3aeBhFX4IqTIMw9rwcxuGxdTbVcPveWC8lGNDqlItsW24BpZlMx+GeDlI973lOnzj6HmHsMh9b7mu7TVPnJ1FqWwg2zCyJME4VqO2rpedZV0ewiInzs7WFV6b7Sx75dWTyEtsCPDfQapl1f10PGvcP36TL05hMzWBmUahMNYy6Q3KsbXZljajcqyXnfEV3pMIY/6K8/7qSbDfXwRBiAcPITpewc6tgkJmO5ijJ9Mors3C0pSqSEWxZODoyXTba17OFF3FSi57PAitMrx3FxRZqvcx1eb4DQ+wiaB4Dqbwo2HKZ2qz/JrFJNgHXPNJ9fAQRgKqB+4PjN+I225IYXjvLtx2QwofGL+R6cBdG6tRKhvQDROlsoGllRLzXDheXwA8hEV47VVVpOocx6Y/rAEeXuWxvEjPZfG3b+pmAAAgAElEQVTCzApmLufwwswK0oyl8jzhITADrCvH1krDZVlCdzzEVBFieAQbDJPt/eXV16kx3rcEQYgJDyE6Hm1fWwllEncwbiV7m9lbXtOlZo1lTYBfuZZumK5iMG5lRttN4yy/jXa2Q7xuWPVB8o2jNXSD7ZDFM0Lmd6anUDLWRz80ZDjyJTbBJV7ZLh7CIrz2Orx3F16cWamWGNproyok9gAPL7EhYF1IYDFTRCrJvm7N6apRc7oAMGfneGT8eAjMANV3QkhTEA5Z9Yx9SFOY3gmGh5Krl71VFjzeX152gtjJUPl19V09f6XgKO9neSeOHRzYUHHVaBcBchKJq0KvmA5Zd8sG80gJXuVatYNxpOmwHcQoDq9DfCoZheXicPixLq9yQL9xGyK/mb1Vxg4O4FvHLjoccNYvAB59c7y+rHgFeAD/S7oBPmXSvJwuXs4nj94boFreP5Otii5JklQf3dLD0pPIqefVK1AYxAAiQfDG9sjYe9l3IhOTS3h+emW9gkeR8fz0CiYml9r+buAZ7NwKyEncwQym4njx5RWHLDuL4h4vEQGAj5ACD/EeXvA6xIu2Lg8cIwokf0YUAM6CZr+K1Xj0zQH+Op61dXn14/GQDufRR8rL6eLlfPLovakiTnk/L7xGwvgkzkwQXKh4lG972XciR0+mccVtFNvJNNP3Do9g51ZBTuIO5ub9vXhhZqWe+bMBSDZw80iv7/9fkm9HY//xW7yHFzwP8SKty4PBVByTs6uQFQmSJNVHtrCOKKiNaWjOVAdVuYxHIIbXurwUaRczxbqIUWPgiKUkkpfTxcv5vPvQvg0ZykY7C43l/aZlB7q8nxeaIrtWKKgMsy27YxpW8s7fOesoJ4Ig1knP52A2OMU2qqPY0ozaBSJDTuIO5twvr6xJkKPeKyQBODd5pe0o9K5YCCs5fb2/C1WBmURAv6waxXuUNUe2Jt7DeqjlkeUQ6RDPc12/aSyJbDy8spZEiq5cFmR4KdKGVAUz2fUe6pqKMMvcUF5OFy/nk0fvDbCxvF9T5bpgDUsJuiJLG75vGu0sRMMKimVnm0Q03L6CMACENMXVSQxp7a+bLxpXZScI4uoxPNpPvOydADmJO5jpxRxkWYLclOVjUcusSZw3rmhZbBLnPOEh3gPwy3Lwwm+hDtFoLInM5HUkY/449SL1ZYpGTZG2PnPPAHTdhMRcuuh/k1vNuTp+Zgb5YgUxnwRmeDmfE5NLmF7MY2B3rG6bXswz9d4AfErQd8VCWF7rc2y2sxAJqa5OYiTEdiwKaTKUsuQIpLIIgHgqvHZQvxhB8EZVZei6850Q1OqzrYCcROKqqEmcN8+wYx16LxoiDUjlNc9QNHj0BYjU8yoavBRpean9Du9N4Lp93fVAzPDeBNN6AD/nk9f7i4dIg1fGkDWT6Jk1YFRN1VS5Xs5ew7ZthBhmnBIEwZ/h/jhefHnVoePBMnpKdMhJ3MEMpmKYnHUehgdTMZe/3RqLmSK642F0x8NNdvbyOh7ZrlovmsPO2IvW2NfUWAoXxDJDkRxaEXGZCOMLnZ791Q1r/VraG+0s8FD7nZhc2qByO79cRHoui/fee4D5d/aO24eZncJmtmJ8jV/BmIxLFnEze6vohunaSc+q1K0pkqsCOIuPSOMJCII/43cMu6qVj98xvN1b2zboDbODGb9jGNGICtOyUTEtmJaNaERluuF5DQatZbvml4uw7PVs18TkEtO643cMoadpKHlPIszcixZSFSxny/VodK2vKYhf2tQ3x48TZ2cRDatIJaMY6IshlYwiGlY9HfNWmZhcwrePXcTE5BXMXM5jYvLK2me250EkvPJErMWmXlleluzv0ZNpZGrvAxv10Q9HT6bbXpMnIg145lVqqSoyJLkaf6j9kWQ2gRkAWPB4r3rZW8Gr3I2ykwThH6MjfRg7OIBIqPpcRUJKxwVnmwneiZbwFb/l+XkcsIDNs10s1HrRRkd6sW93HKMjvWufWR96TsO7OMDzQDgxuYQnfjiBz3zzGTzxw4mOcmIAfg740ZNT60EIez0IcfTUFNO6IqF5HNZZ+0NGR/pw+K796O+JQpYk9PdEcfiu/UzvBF69z7wYOziAlVwZ0ws5vDSfxfRCDiu5ciDLpL2qSllHSvQkQrCt6ndi7Y9tVe0s8Ji/WHbpnQSAUpmEawjCLyYml/DU2VmU1voSS7qJp87Odty5phEqN93BHD05hUKTsmehZODoqSlfBoP6OfZgK8qf/KSxr8k0baiqP31NPOA1z5B6HfkJ10wvuotLsYhOiYaiunsBrJkeQBxVXl6k57LIFSrV3jkbsGEjV6ggPZcN3HUJaUr90NZsZyEWCUGRi1VhpDX1b1mSEIuyOYk8MD2Cj152giCunlpwtkZjcDZo78WtgpzEHQyvgyaPAxZPlUgevV2NfU1+Sb3zgpdjT72OVUfbrYchiBkZ0ZAlCaosraubrtmCOJedV+8zwOf9dfzMjKvy9fEzM773P7KiKTJK8F9xUDdMxLs0ZAsV2LAhSRLiXcGc6ShBgu1SvcKu9EsQRA0KzjrZdicxm83ioYceQi6XQ6VSwcMPP4xDhw7h2LFj+Ju/+RsMDFQPWw8++CBe85rX4C//8i9x4cIFhEIhfPazn8XQ0BCeffZZfO5zn4OiKBgbG8OHPvShbf6piKtFtGwXr/3ygodjL1qvI4+5loD/Jd0AH9EpnvBwZDRVrjsykiTVFSO1APZhjd8xhG8cPe9QfWbtfeb1/soV3RVi8x727aTkISTjll28GkKq7Fpp098TPMdLVSXoFaeTqCrB2ytBEDuHbXcS/+Ef/gFveMMb8P73vx+//OUv8ZGPfAQ/+MEPcO7cOTz00EN429veVv+7x44dg67r+O53v4tnn30WX/ziF/H444/jU5/6FP7+7/8e11xzDf7oj/4I586dw80337yNP1UwEOmgKVq2i4fUOyCWomUqGcWFSxnkGg7G8S4NN1yT3O6tOeA11/LE2VlEwioiTUqZrPeXSCprvByZof4EbBuOku6gypGHNAXhkFX/fbGWQwLV+6hYNhz3Aev9FY9qyBWcDmEsqrFslwuWh0CNl711JFiW7Sg3DWKqmpeIE0EQ64h0Zt4qtt1JfP/7349QqNoDYJomwuHqaIVz587h/Pnz+OY3v4mDBw/iox/9KE6fPo03vvGNAIBbbrkFExMTyOVy0HUd1157LQBgbGwMp06dekUnsaenC2oAI9LNpFLtz9r6vf92E/7HP/9/WM1XUDEsaKqMXTENv/ffbmJalxdvTiXw5tcN+7rmck53LUvK5HXma+D3fv/PhQX8aG1wtqLIuJIt40dPpdHd3YVbb9jj2/+PXyTiYazm9fpny7axmteRiIcDd389828XNtwHtf/+zwuXmX6HvO6vN6cS6O7uwk9/8RLmruSxtzeGe153bSDvg+ZrW4P12o6/8dX4n//vc46h6eNvfHUg769dsZBjr6zXYPpyHiu56jMmQYJp2ljJ6Zi5nGe6BuNj+/GdH1+AadnVUktIUGQJ42P7fb22fqylKBsH0zfaWdbPliqQZAkwAUjVgmZJlpArVrjdX+2u6+UO2wxrvhK0rlh7FW3dIO51K87MQfvueiW21En8/ve/j29+85sbbJ///Odx8OBBLC4u4qGHHsIjjzwCALjzzjvxa7/2axgcHMSnPvUpfOc730Eul0M8vh5FVhTFYYvFYrh06dIr7mV5ueDTT8UXljlT1/RG8Yab9+L4mRnohomQJuMNN+/FNb1R34aJB52eeMi117G/x79r4Nc8sKP//mK9t7HZfk2vu0LpdnLmwgIUWXIMnj1zYSFw99f0/Gp9dlljD+ml+SzTXnneX9f0RvH+t9+wwRa06wpsvLaNsF7ba3qjCKky/u/UMiy7qmb5K0M9gXx/8boGpbLhGMwOAMWywbRuKhFCLKpW+/HWsmixqIpUIhS492JYU1z7BMOawnxtJdRKNtdzcqzXdjPaXdc0PYRrTDtwe91J64q0V9HWDeJer+mN4t33XO+oaPPrO8evdyIPvJzXLXUS3/nOd+Kd73ynw37hwgX8+Z//Of7iL/4Cr3vd6wAAhw8fxq5duwAA99xzD3784x8jkUggn1+XFLcsC/F4fIMtn8/X/12nMzG5hNMXFpHoCiHRVY1wn76wiOG9icCWMPqNSL2DovX45YoVyJIEuakvJoh9TbyEkXjeX6KUHqeSUUzNZZFtKIlMRDUM7WWLmH796HN4Lr1c/2zZwHPpZXz96HO4f/wm1m37Cq/7i9d8vBNnZ9EdD6M7HnbYg3aPeanZsqrcijR7kF/JLUEQjXS68nUz2z4n8YUXXsCf/dmf4ctf/jLuuusuAIBt2/jN3/xNzM3NAUC9fPTWW2/Fz3/+cwDAs88+iwMHDiAej0PTNLz00kuwbRsnTpzAa17zmm37eYIEr9mDIjE60ofbbkghW9Axu5RHtqDjthtSgXwJiDTgGqj2NbkRxL4mXvM9eczcA9b7/OaXi7Ds9T6/IM5rGtwTd53pyKrs+fRz81dl30543V9D/Qn0JMJQVRmQAFWV0ZMI41rGvkyRAlKGS3UFABgmmwopr2vLA682yQC2TxIEsYPY9p7EL3/5y9B1HZ/73OcAAPF4HI8//jg++9nP4kMf+hAikQhe/epX47777oOiKHjqqafw7ne/G7Zt4/Of/zwA4K/+6q/w0Y9+FKZpYmxsDL/6q7+6nT9SYFjMFF1FD4J4EOCFSNlUkbKeAHD3oX04stZD2WwPGryEhmpr+30viTReZHohV58Z2vieYZUNNzxK7Lzs2wkv4a2xgwOYXy46hJFY3wk8Rw75jW64q5jqHqqnrTJ2cADn0ldQLBmwAVQqFiSJ/dpKEuA2vpDFoQtrCoouaq7hUPCyngQhMqJU8GwV2+4kPv744672sbExjI2NOeyf/vSnHbZbbrkF3/ve93zfm+iEVBmXVkv1njHDsKBXTPTEgzcsmBciHbZ5HTR58Y7bhzF/pYBnzi+gYlrQFBmvvXFP4OasNSPC/GmRMj2Lmeq80GiTI8O6Vwnugh1BTZ7wCBbwdD5FCkjx4Onn5pEvGvXPNoB80cDTz81zeeey3Le74iGUrhQ3PA8SgO5Y2OufEARxlfBS6haZbXcSCX7kS8aGhncb1Ub3fMnw/kc7DJEO24BY9fATk0uYXsxjYPe6PPT0Yh4Tk0uB+xl4jcDghUiZHl577esO4/JK2dXOikjRYpGcT8D/eaSy7O5eedlb5ZnzC66O2zPnF5h6XhVZcs12s+xXU2RHwMQGzUkkCD8RKamwVZCTuINZzpahKE71yeWs8+C1UxHpsC0aIr1QRdorUM3ofPvYRYcYTBAzPbyyUv/97b+CJ354rl4OKAGIRlT897f/CtO6FC2uwsP55BGM8cr8s1YEVDx6Gr3srcJjpuFKXnf99ysNI4gIolPgUdIN8Esq+B0420rISdzh2Dbq0uw21sZBdRBUVsUPkbK0Iu21hlvmIIjwykqNjvThgd+6ud5Hmoz58+UqWsBAJE6cna33wZumDUWREI9qTNfWbQTIZvZW0RQZuosoTohRNVWWJcDnTGK5YlbHDdl2fWSJLEnMfZkEISIhVUbZZSxOyEOxuFV4JBVEq2JqhpzEHUw0rDhKS03LRjTcOc3uovX5iVQGJ1KWVqS9AtX71a3Pj9WR4XV/8S6T9rOPVMSAgShMzWeRWatUkSQJhmEhky1jiiHEH1Ld5ySGNLbvsesGuzeMWGm0sxBSFfcDLMN+41ENuUIFclM+MYhK0gTBG7fnazN7q/BIKogelCQncQdT1vk8SKIhSp8fzzI4Hs6BSFlakfYK8HFkRCuz5BWB5RUwECnAw4uKx7iKiodCaSt0RVUUdcPRNhGLsDlI8aiGrojqKGf2Gu3TKorq7hCzzHUUSUmaIESFR1JB9KAkOYk7mKLuLlBTKgezRKXTD1m8Ik68nAORsrQ8R2DwgIcjI1pEk0fpIsAnYCCaA84LHgPqh/oTgA1Hf64fsyLdZtOyHt5kSYLqogXA0i9VU4w+fmYG+WIFsaiGuw/tC7ySNEGIht9JBdGqmJohJ3EHI0sSJJdOpiAO4KVDFr+IE0/nQJQsLbC+11QqgcXF7HZvZ1N4ODKiRTSn5rO40jDCRzKqs/EkxhcYj+CGaA44LxodOtOyfXHoxg4O4OKlDMq6Ccu2YZo2Qqoc2FmRmiq7agGwOMpA1VEkp5AgxEK0KqZmyEncwXRFVWSyTvWzrgD2MfA8ZImSoeR1aBHNOSD4ODKpZBTpuaxj6P3w3oRf2/aVQrFhhM+amp1p2iiUKsxr+x3cWMwU61nPxmvbac/Y2MEBzC8XEQmr0FS5Xn7KciBKz2WRK1SqQjU2YMNGrlBBei4buIwyUBXEMa2NwdmqwxzA6CwnRJtxSvBBltaDJc32TkG0KqZmyEncwfQno8jmKxu+sBRZQn8A09w8pYdFyVCOHRzAt45ddBw0gxoxJ/jityMzuCeOZ5+/XP9cExUZDGhE03NEgUff23YSUmXMNIwWql3bnnhoG3e19fA4EB0/MwNZlhyiLcfPzDBl1niVy/MaV3HkVBrHz8wgV6wgHvByU14jCgixcHMQN7MHAR5JBZGqmJohJ3FHI0GRq382moP3publyIhWBtb8m/HjNyV6uQPhD9MLOfQkwo7erumF3HZvzRVFljbOeZWqvV2O91kg8NhTAN+1vPH7QJQrumeO8x729vDv1FqumJCaMiiyBKZxFUdOpTcI1+QKlfrnIDqKIjoHBCFSUmGrICdxB6Mbpuuh0E1OfLvh5ciIVGp54uwsImEVEZ/HHogkMMMTXgNtRSlnXswUXe+vID4LADCYimFyNgtZkSBJUn0u3mAqts07cyLSu1Y04lENq3ndIQSzq4stSzsxubShcmN+uYj0XBbvvfcA0/Mb1hRUKtaGsIFts43AOH5mxtMeRCeRIEREtKTCVkBO4g6mlp1rPhQGscyQlyMjUqklT4dWJIEZHvAapyBS5FGkZwEAxu8Yrh/iTdOGqlbLr8fvGGZe22/HXqR3rWjcONSDp/5rrv7ZBmCZNm4c6mFa9+jJdH2mI7BeInz0ZJrpXuiOhZArOLOc3bH2ndpcsQLLth2Osr/ZVILobHi2PfEIUG8F5CTuYEQrM+ThyPDq8+OBaId4keAVIRRJcEnE98F77z1Q729Lxvz5cuXh2It2bUXicqboEMCQpaqdhenF/FXZW0VTZYRDCkr6enlpJKRAY1A3DasKsg0OYc1RjobpCEcQfsHjDMYrQL1V0BtmB0NlhlV49PnxgA6a/GhUn2ycuccaIRRJcInn+4BXyS2Phn8ejr2I11YU0vM5Ry+bZVftQaRiWBscRAAo6SYqRvs9ieGQjKzLqyasuc+lJFqHFDiJGmMHB/CNo+eRLVQz97IkIdGl4fBd+9teU/QSVnISdzidXmbIq8+PB3TQ5Eej+qQkSb6pT4omuMTjfSBSyS3Az7Gna8uHiofgi5e9VQZTcUzOrjrte9qf6QgAS6vu95GXvRWKZROyDFgNLa6yXLUTbKiKDN1FMVlVyQHvNGojomr977ZtI1dkG7cjki6GG+Qk7nA63TkQbX4ZHTR5wUd9kgSXxIuUilTWLdq15QKneQrjdwzh28cuOsSGxm8fYlq3OYv4SvZWUWUZIL/FdwwPyVXDJCnWTuP4mRnIkgRZ8W/cjkjfN27QK2cHU3MO5peLsOx152Bicmm7t7ZlhFQZmWwZhmEB9ro4QUjtnFqSzQ6anUJNfVJVZUCqRol7EmFm9cnRkT4cvms/+nuikCUJ/T1RHL5rvy+CS6WygcVMEbNLeSxmiiiVjUB+sYjk0ALeDnwQy7pFu7Y88HpTs77BR0f68Pv3HsDoSC/27Y5jdKR37TOj8+3lWzD4HF6KvkFU+gW8SzWDWMJpeTiJXnZi58Jj3I5I3zduUCZxByNaFJpP1pPml9FBc6P6pKbK9YHsfjhdPLK/boPvl7Nl3BnAL5ZUMlov02nM1g/vTWz31lwZHelDei6L42dmkC9WEFsbTB7Ed6LoUWg/8HpV+/EK5/HsyooE0yUL1ZyduBoalX4bnzE/lH55QHMSCZ5wKi5APKphebW8IZ4jAejZFW57zcY2okxeR3+PWBV9lEncwYjkHPDKevLKIIlEKhn1sHfOQVO0aN70Qg7Jpvs2mQgHcvD94J64a7aetbeLFxOTSzh9YRGJrhD29sWQ6Arh9IXFQFZYiHbfbiVSQCXIQh69bF72Vhgd6cP1g90wDAsVw4JhWLh+sFuYgyZB+Inm8Sx52VslHtUcCX97zc7C6EgfHvitUXz5z+7CA781KtRzS5nEHYxIUWheWU+aX0aqqYB40bzFTBHRsOqQuA9igGd6Iec6SD6IDi0gVoUFKVQD0ZC6YfxDjUi4/ZESNXhUr3hly9wyH61y5FQaT5+bh2Xb1UCMaeHpc/Po7+1qu1eKIIiNzC0VrsreCZCTuIMRyTnglfUU6Rrwgg6aVXiMU+AFrwAPj0PxYqboqiAcRIcWEKvCAiCF6u645uokdsfYovu8BL1UWYIhSzAbvEVFlqAwNOQ9+cylDQIrtg1Yto0nn7lETiLRcVQ8KsG87C2va1qu9QkVs3Mqz5qhctMdDC9RDR7wKokU6RpsDdQUIgI8ygx5lXSLJLIDUPm1aFRM2yF4IksA4wQMboJePYkwLMuGBNT/WJaNnkT7fU25grtwhpedaB1ewkgEPzhoQwEANEWGvbZO4x9N6VxXiTKJOxxRotA8M36iXANe0AgM8eCR/eVVZimSyA5A1QU1RBmPVDGqJcxOO5uXyCujHIuoUBQJlmXDRtXZkGUJsUj7xy1eh2Je3DTcg+fSy672oCHJgO2SKJI71y/oWK4b7Ha9b68b7N6G3QQDchKJQEAlkfwQqQeLWMfv4AavQ3FNZKdZeTGoPYn0rqk6iI0zAueXi5iay/ozAsJnvMQoQipbTyIvVV7dsNC7K+JYVzfad+l4qTny4qPvPoSPPXFyw7sllYzgo+8+tI27cicW0ZB1ych2RdjKmQnxiEc1xCIqCiWjHuDpiqjMwjUiQ04iERg6PePHC9F6sAg+8OpzFElkp0anv2uOnpzCcrZc/1zL/h49NRW46zLUn0BZN5EtVGDZNmRJQqJLw7X9bOq5bhnwTLaMQcaMcioZhbVcdDwPLM+ZIkuuw91Z+hx5cuRUGsurZchrzq0kAcurZRw5lQ5cD2V3LOTqJHbHQtuwG6IVZMldIIr1cVjMFLHbpR0hyN9lvKGEOkHscKgHiwD4jVOg+0s8phfds7xBzP4O7omjUDKgyBI0RYYiSyiUDOYRKzVV3ubxSKzXgMdzZnlIo3rZt5ua0I5VFWOFZQOGVRXaCRrLubKHXd/inRCtonj0CHrZW4W+y5yQkxgAVI8hu1524uqYmFzCEz+cwGe++Qye+OFEIOeh8YRmrREAPxEnur8InvBy5hYzRdeZaKxZg9GRPtx2QwrZgo7ZpTyyBR233ZBies68fMGA+ohCCe0US4aHPXh7Jdbg9EDQd5kTKjcNAJIkwa0FXQpqw4FAkGgL9WAR6/Aos+R5f9XEVZZzOnriIbpvfWIwFcPkrHMMzGAqtg272RxeI1ZCqoyZppLbTLaMnjhbmeHE5BJOX1hEoiuERFd1rdMXFjG8N9H2vStLEkyXA7Ac0DOCSEI7XnMtvewEO6x3rVvp9Wb2VqGzkhNyEomrRhRVPIBEW2p0eg8WwRce91djgEdT5Y4M8PBi/I5hfOvYRYe4yvgdw9u9NQe8emk9j6qMjheP75yBvihmFp0DvQf63MvjiNYRTRRIJGQZsFyUYyXGGkaeQQg6K22EnMQAYHoM6vSybyeiZeZItIUgxIQCPFV4BOVGR/rw3nsPCBExHzs4sEGJVVVkJKIacwmYbpjoSYQd6+qMA7l5fOfc95br8fWj55FrEO+Jd2m47y3Xt70mUcW9jovmJPqBm4O4mZ0IHuQkBgCRyh1EO7jxi0ITBMETCvDwDcqJFDF36x1kpfbd0FzGyvrdwOM7Z3SkD/eP3yiEUw+IlZ0TqTSWILYaEq4hrgrRDm7UiEwQYkJKc5sH5TqFE2dnEQ2rSCWjGOiLIZWMIhpWma/B2MEBlMoGFjNFzC7lsZgpolQ2mL8b+H/nBN998RrNEcSRHaKJAhHewYYgBiFEZ9szibZt401vehOGh4cBALfccgs+8pGP4Gc/+xm+9rWvQVVVHD58GPfddx9KpRIeeughLC0tIRaL4a//+q/R29vr+ncJPoiWmaNGZIIQk7GDAxuyaI32TkG0oBwPeF4DHhnK0ZE+PP3cPJ45v4CKaUFTZLz2xj1M3zmitXmYHgIiXnaCuBp4OvYiaW5sBdvuJL700ku4+eab8cQTT9RtlUoFX/jCF/CP//iPiEajeM973oM3v/nNOHLkCA4cOIAHH3wQR48exWOPPYaPfexjrn83lUpt40+1cxHx4CZSWRVBEFUaAzyZvI7+ns77whYtKMcDXteglqFsHnrP2jpx5FQaz5xfAABoa3Pbnjm/gP7errYHyYvW5kElnISIiBaM2Qq23Uk8d+4c5ufn8b73vQ+RSAQf//jHoes6rr32WnR3dwMAbrvtNvznf/4nTp8+jT/8wz8EALzpTW/CY489hhf/f/buPEyOqtwf+LeW3qa7Z0nSmSQM2RBQSAKJMQoJW4QbJSgqRgEFr8KPiw/gRSECgkQEWeQiXkAE1weVewm43CBBRcAQQ3LZJORO0LA4MzAhmUwms3T39HR3ddXvj073LF0VZub0ma5Kfz/Pk0fn0KnU9Fb1nvOe933zTdvHfvSjHz3gv9vQUANd1+T+cmUQi0UrfQrDnBKLoq6uBk89/xZ270ti2qQwPrxkJhYdObXSpzbh/rZjD558/i3s7kpi2uQwTq3S58GL3Pa5InunxBMgqRUAACAASURBVKI4ZcnsSp9Gxaw84TD88vFXbce98B4uxznKeg66Exn49NIdNz3JjNBxN76yy7Z91V9f2YUvfnz+uI4p61wPpFqOq2uKbesEXVNcd64H03HdeK4v/HEH4v1Z9CXTyJkWNFVBbTiAF3fsLdt1yAvf20NNaJD4yCOP4IEHHhg2dv311+Oiiy7CRz/6Ubz44otYvXo1rrnmGkSjg09kOBxGIpFAIpEojofDYcTj8WFjQx/7brq7S8tJV8qBqmt1dpb2sqq0QyeF8K8fOXLYmBvPU6aR5fnf2t2Hnz3ajN4yNCcnuWKxaNW9X2WTnaJTra/ZoZNC+PjS2SXp8odOCrn++SjXaybrOWiI+G1XKBsbxI7bl0zbXtD7kulxH7ch4kfb7nhJJdZZ08Se4wMVmJH1/nLbcVWHPtWqqrjuXA+m47rxfdv85l50D+2dmrOwr28A//fm3rI8B26+jjkFrxMaJK5atQqrVq0aNpZKpaBp+RW9xYsXo6OjA5FIBMlksviYZDKJaDQ6bDyZTKK2ttbxsV6iqAosm1Kmigs3eVOe19J/iGRhio5cTJeX8xwsWzDdtlek6NaJSMiHRH+2ZDwc8o37mE1TI9j6+t7iz4ZhojuexlLBc9VU+1U0NxaYkcVwaDVmGOzTIEpV7Kv0q4IlM2W9b+P9mTGNj1ZhErU7kUFDxO+pbRMVr256zz33FFcX//GPf2DGjBk47LDD0NbWhp6eHmQyGbz44otYuHAhFi1ahGeeeQYAsHHjRrz//e93fCyRTCwoQZTHCpwkW3NLF+5b14wbH3gB961rRnNLV1mOO/KWshyh0ckLD4FpWjByJrKGCSNnwjQtnLzwkHEfs31PAvXRAHRdBRRA11XURwNo3/PuWVMHknPos+U0TjQWPp/9li6/4FYvuwDxQOOjJaPgUmEStaM7BcuyipOo5foOk63iexIvuugirF69Gs888ww0TcMtt9wCn8+Hq6++GhdccAEsy8JZZ52FxsZGnHPOObjqqqtwzjnnwOfz4Y477nB8rJeYDl/ITuOVxupPLChBVMAJE5JJ1kr1pm27bKubimaDzJ4WhaoqMIz80S0rv79t9rTxZzh19qRsi+yIfsbY/iEfcGeypauGus0eUBobz61HH2jv1zh5Peus4kFiXV0dfvSjH5WML1++HMuXLx82FgqFcNddd43qsSQHU8vyvFjllUgGTpiQTLJusto64ugZuv/IMNETT6NNsNnaL/64A5kRqYoZw8Qv/rgD3/3y8eM6Jj9j8nipp6PXOKbyOoxXmqooyNnMkKgC3wlen0SteJBI3uL1WZFyYXl+Kqj2lXVOmJBMsm6ysg57zrJGTui4Xb325+U0Phqy9k+S8/uAexLFyUoLlcUpFhQJEmP1oWLRqVzOgqYpxaJTXsAg0QUOVKnJbTp7UkiljZKLlVdmRWSoptQcGo4r68MnTIZWn6yW35/kkrWK5tNVmJYF07RgIZ9RpqqK8H4pWT0CM9kc0pkcTMtCLmfBz3TI8mDKLe1XG/ajL5kp+U6IhstTdEpRlLIVnZooDBJpTPy6ip02KToNEX8Fz2rijWyBUY3BAXFlvYAVOEkWWSvV9eGA7epeneC1TFcVGDb1BHSB9MX1m1vRP2BAUxVo+zdI9Q8YWL+5lZ87QYpDCU5Wl68+Jy88BI9uarEdH69C0anE/pVEXc8vrIgWnZooDBJdwFubxxXb2VdXLntKxOCAAO/vNyByO3kr1RZURYGqjbh2CV54Z8TCeKuj9AZwRiw87mO2dybHNF5pEup/SKOpCkoblnBPYjWaPS2KSMiHeH8WlmVBURREQr6yFZ3y6Woxvdkr9wgMEmlMepJp2/HehFgfGa9hcECA9wpKVPv+SfImGSvVGcMszvAP3TqRMcSCxEQqW9IfTlXy4yJypjWsNYWmKhh/EpxcslJuZXCa366yeW9CfiKqLhJAXSRQMj7e7x+v3SOMxCDRBbw065Y1TNvZ14zgZn+v8foHvxrJaGgrs2hLuQM67p8kGhSrD8HsTpW0lRD9Ds8HifmrumXlgw1VUZAUCBJDAR3JAWPYWM60Ss59rLx07yGL14qrkLz3rYzJf68XdmOQ6AKKClg2hbRUF+5L9zlslvcJbvYHvLXK4fUPfrWRtYdUViqcjICOKdLe5KXvRVke29KKDS/vRCKVRSTkw8kLD8EZx80WOqasiqEBn4ZEdjAgtCwgZ1kIBcd/u9XXb5+p4zQ+aowSnRuou7RPNclbqZYx+e/1SvgMEl0gHMznQI9UExRPJin3DcasxigsCyUX1lmNEeHz9NIqx7w5k9G6O44NL+9EcsBAOKjj5IWHuPJcSW6AJCMVTsb5MkXae7z2vSjDY1ta8dizrcWfE/3Z4s+igeLIWKgcsVFd2G97Pa8Lj78gjl2z9wONj5a36iHIYTmEFlY1PQkEQN7kf+EeIRaLorMzLnSsiebCtarq43RhEs2JL9xgdHSnYFqDNxjNLV3jPuayBdMRCuiI1YcwfXIYsfoQQgFd+EN0oJtiN2pu6cJLOzoRrfHj0KkRRGv8eGlHp9BzS/J4LUCScb6x+pDDOFOk3cpr34sybHh555jGR2vTtl0IjriWBQO68HObzZklRU80VWH6oksxUJbHqfaPW2sCzZszGe8/MoZ4fwa7u5KI92fw/iNjVTMhZ4criS4wcq9BcTxlPz5aMlYjZKXXee0mnql73iKzoa2MdEAZaS9MkfYer30vypBIZW0raovs8QPyz+1A2kB8SFZMtAw9f7NGPkgcGSiK7Nt36NLg2pttojxv5TMXruUDmRwsAAOZHDZt24XZ06JVe1/HINEFTIcpK6fx0ZJ1gyEjvc5rhWB48+YtshraykoHlBHQsem993jte1GGgK4NqwxqIb+PTLRoi1/X8HZfohh8GoaJTDaH+mjgXf/ugfh01TaoFdm3r2kqTKM0tVTTxJLBhpbkHzlOJEpVAdNmbsSN9TaAfD/SHps+4NXcj5RBogtoigLDJiDUBPNNY/UhtO6Ol+wfFOn5IovXVjl48+YtshraylpRlhXQsem9t3jtexEofxXhuojftn2EyB4/AEgOZIalgFoAzJyFZEqsGEx92I+uwmRhIUq0gPrw+GsM+HUVpk0LDL9gMDd3ehRv7OwrOe7c6WL3CIpin67JthLVxbEokEtTr73Wj3QiMEh0gUBAg2GTWhoUnCkdunoCDM6KNLnwBsNrqxxevHmrZrIa2spcUWZAR177XpRRRdinq6iL5IvBmJYFVVEQrfEJV9Tu6Lb/jDqNj54CVVWgjkypE4iQmmIRtOzqK0lhbZoqVjBu5fGz8dP1f0diyHMbqfFh5fGzhY7r01RkuEJZ9bzUL7PALgugmjFIdAG7dA9AvPdg+54EGqKBkj0XoqsnsnjpptjrZY2rjayVX64ok2xe+l6UsbIeqw/BtFDS4Fr0M+Z03XUaH62MkbO97opUIl15/Cz8bP3fSwLllcfNEjpXQE6FV8fgwM3RAVW9hmhg2KphIbtg2iSxFHQvY5DoArLKW3f2pBAM6CUrktw3Vx5eLmtcbWSt/HJFmWgQm1EPThyNvO6KBrUj46tyxFvrN7ehL5kpFsXJWRb6khms39ImNDFhOvQYdBqvJE1TbNMfNa26V5CqkxfXPuXi2v9BjCXvifLmzZmMs06ai8aGEFRVQWNDCGedNLcse/yKx1XKd1wiL5JxzfHaZ8wpeBUJatdvbkVqwICmKvBpKjRVQWrAwPrNreM+JgC8+U5vSdVU0wLe3NkrdFynFD03pu6NTOF9t/GDlWMrtgk9i8rqjmegqwpUZX+qqQLoqoLuuNg+ZS/jSuJBzGszsEQyyVr59VI6oCwy2oCQ98huRl1OoYCGVLp0S0coILbXUcY+UlkFNZx6N4r2dNQ1BVmbDl66C1fnZD0HXsM1tDzb/cRVjEHiQUxW0QPeEBJRgaw2ICSXjO9xL+3V/uiHZmHdX1tKKnt+9EPi+/wGle8W2zQtmJYFy8rXwFFdXCrUU4GX00ZJbqB0LV1TbN9LopMQhQJRJeOCBaK8jEHiQa7cM7C8ISSioWS1ASF5ZH6Pe2Wv9hnHzQYAbHh5J5KpLMIhH05eeEhxfLxkPLcN0QB2Di2oYeX3DzYI9nSURVZRIBl0XbWt/6CzEqtryYrrZRaI8ioGiTQmvCEkoqFktgEhOfg9nnfGcbOFg8KRZDy34aAPmqaUlOYPh8bfe5HyuCfRe3IOBZCcxsfC79MQ8JvFysR+n1j6udcxSKQx4Q3hoHI3jfYiph6TF9uAVPv7lt/jeTLeB509KQykjZIWGCLPbcbIYXJtsKxtNSgvZ1pQFQwr4KMq7qzESnJx8qwUg0QXkJVfLYMXbwhlkNE02muYekyA9wpk8X3L73FA3vvAr2vYGR9MDTUME93xNOoFUkNltdUgIKBrJcG2aaHqV5CqUVtHHD3xdPFnwzDRE0+jzcX7f2Vj0rULRGrsU0aiNf4JPpN3J6O8txcdaMZJRHNLF+5b14wbH3gB961rRnNLl9DxZJL1HJC3eK1FAd+3cr/HC99hX/v+M67+DpP3Pij/hiled+Vxuv+v3rCgejnvpS2tglwtuJLoAjnDqRKY+1JJZFVM9RoZ6VpeW+FgyhoVeKkNCN+3+derdXccG17eiUQqi8j+oi3lqHztlQwLWe+DjGEiFNSRGFL8IlLjQ8bhOj8aQ1+voUV2RJ9TVQVMm9sMTXD5wEvZUYmUTa8OAIkB+3EaPUWxnxtx68Kcz6FYkV+v3lVlBoku0J/O2o8P2I9XmpduCGWRka61adsu270sbs2HZ8oaeRHft/lg7qUdnYjW+IsZKy/t6MTsaVGh7xov7emJ1YfQujuOxJDv20jIh9nTokLH9etqsfG9tn89KjVgwN8w/jtjWa9XOOBDPFV6n1ETFCuIUx/xY29v2nbcbUyHFV7uSaw+sxqjgIWSe7CZjdXbAoPppi7gtGDowoVE2m/ZgukYSBvo7Enh7Y5EsViBSPpPW0cc3fE0DMMErMG9LG91JMp45uXDFCjyIr5v5aVaemmVtmlqBD0jvm974uky9ERzyl8cf5C4adsupPZfb3Z1JdHZk0IqbQi/XgG//S1gwCd2a6g5LEVqmtiKTE3A/u87jY+GUxFTFjcV57XKscsWTEcwoCNWH8L0yWHE6kMIBvSqujaMxJVEonEaOc8oOu/olA+fcWk+PFOPyYv4vpUXzHlplbZ9TwIN0UDJqkH7HrFJuYyRsz2uSCXSto449vUOwLQsWPsD2kwmB0Uwb683aZ+t5DQ+Wv0OqZqi2VEDGftrodP4aEyqDdiuek6qdWcPSi8J+nUkbFaqg353hh68NpRy5ytF5HKbtu1CKKAjFNDh09VigCeSVuWUD+9zcT48U4/Ji6r9fSsrmPNSpdvOnny10JEVQ8sVKJezEmn/gDGsB5xlATnLEg66DIeJSafx0ZIRzAHD21SMZnw0JteGsK8vXdICY3JdaPwHJQBAzm7D6wHGR2tky5Kh4+VTvnRjL7dLY5BINA4yZuJnNUZhWSjZIzOrivPhiaj8ZAVzQ2fie5IZNDaUp/egjH6GXgqUM45VFwX3pCiwvxcWvNl22s/nxn1+PcnSVUQA6ElkJvhMDj6ptP2kgNP4aPl9mu2Eg2jbEhnFA71UzMsOg0SicZBxg7FswXR0dKcQGjED7cZZeCLyLplpVYVV2lgsis7OuPDxZFV9nohAuVzPra4qyGkKTNOChXwMp6qK8N6uoF+zvWEP+sVutlVVGbbyOXTcbfoSmZJVKdMC+hyCR6o8n6ZiAKXvW6dsrNGSUXhraEHCXM6CpimuLkg4EoPEg5yMGViSc4Mh88btsS2tJeXuzzhutvBxicibvJJyK6ti6sTsPyrPyllTLII33+ktHRcsshMO+myDxLBgdVNdU5C12ZboxhYYA1k5qbEkTypjv+c1lRZrW1IoCDUym0skQ6xQkBAAFEUpFiQU3U88USoeJP7oRz/CX//6VwBAX18f9u7di2effRY///nP8etf/xqTJk0CANxwww2YMWMGVq9eja6uLoTDYdx2222YNGkSnn76afzgBz+Arus466yz8JnPfKaSv5JreK3vnpfISquSceP22JZWPPZsa/HnRH+2+DMDRSJyM5kVU2V838q47h49d5JtkHj0nEnjO8n9UmmjZH+XqojfbEtLj5XAoQOG4zhVnl0PzgONj5ZfV7EzPriCXKh43CDQusVrBQlHqniQeNFFF+Giiy4CAPzbv/0brrzySgDA9u3bcdttt2HevHnFx/785z/HEUccgcsuuwzr16/Hvffei6uuugq33HILfv3rXyMUCuGcc87BKaecglgsVpHfx0281LPKi8qdVgXIWfnd8PJOx3EGiUTkZrH6ENp2x0uqhc4S7Gcoi4zrbvueBCbVBktWOEQrsRqmZZtqaQjuHcxJuoknkqv87Wt8ugrTskpSxd1ckHAo1/RJfOKJJ1BbW4sTTjgBQD5I/NGPfoRzzjkH999/PwDgpZdeKv73E088EVu2bMGbb76JmTNnoq6uDn6/H+9///vx4osvVuz3cBMv9ayiwRnoju4UTGtwBrq5pUvouHYlqAEg6TBOROQWTVMjtv1jxfsZyiHjuivrWu50A+jCrYPkQU5vI7e+vTJGDjVBHTnTQjZnImdaqAnqQu1r6sN+235p9WGxlO6JMqEriY888ggeeOCBYWM333wzFixYgPvvvx/f+973iuMrV67Eueeei0gkgksvvRR/+ctfkEgkEI3mZw/D4TDi8fiwscJ4IvHus2sNDTXQPRDJx2Ljny1taqzFrr2lz8WMKRGh4/5txx48+fxb2N2VxLTJYZy6ZCYWHTl13Mc7GIg8nwUv/HGH7cbrF3fsxSlLZo/7uLXhAOLJ0kpttWF/Wc7bi6r19/YyvmbeU47XrLM3jSn1QfQls8gaJny6itqwD3t70658T8i47oZDfryztx8AoEBBLmehN5HB1IYasefA8W5dkfbcihxXUezTQBVl/Mc9UDsFNz4HXjquoiqwHAoYue1cgfznrH1PsvgesywgmTLQNNU37uP6fDo0TcXIaMPn1135/TXShAaJq1atwqpVq0rG33jjDdTW1mLWrFkAAMuy8IUvfKEY/J100kl49dVXEYlEkEwmAQDJZBK1tbXDxgrjQ4NGJ93d/eX4laQTSWP8wJFT8JvdfSXji4+cMu7jjtxv8dbuPvzs0Wb0njS3alNYy5Vu2t7RZ3uxersjLnT8E4+ZPmxPYsEJx0wvW5qsl5QzPZjk8nJ/qWpXzu9Fn65hct3w2yzR70VZPnDkFDzYtq8kPXbx0vFfd7PZHCyb6Chr5ISeA+e+g5a051bkuAfaPzje4wYcKrwG/JornwMvHdfuPQu49/3VEx+AkRtcNbRgwchZ6IkPjPu4yVQG9RF/vrqpaUFT89VNk/1ZV31/OQWsrkg33bx5M0488cTiz4lEAmeccQaSySQsy8Jzzz2HefPmYdGiRXjmmWcAABs3bsT73/9+HHbYYWhra0NPTw8ymQxefPFFLFy4sFK/iqvMmzMZZ500F40NIaiKgsaGEM4SDOYOtN+CxMTq7Zv3ivbtOuO42Thj6WxEanxQFCBS48MZS2dzPyK52tD0a8uyypZ+Td4i63tRJpvsMiEZI4eGaAC6rgIKoOsqGqIBoTQ4wDmttJrSTWvD/pJWIpqqoDYcqNAZHZiXXjPVYS+f03il5auO5j+vhT+KgmJ10vGI1YcQDOiI1Ydw6NTIkJ/d+/01VMUL1wBAS0sLli5dWvw5Go3iq1/9Ks4//3z4/X4cd9xxOOmkk7BkyRJcddVVOOecc+Dz+XDHHXfA5/Ph6quvxgUXXADLsnDWWWehsbGxgr+Nu5S7ehv3Ocojq28XsD9QZFBIHsLCW3J5pT3SsgXT8asnXisp2uLW/rGbtu1CKKCX9LsVed8W+vIGRxxT9EZTVpVIL5nVGIVloeT9NavRnXteNU2FaVMxU9NcseYzTEM0gL29pfeGDVF3BuAZw7Qt5ORUrXc0ZN7XTQRXBIlr1qwpGfvEJz6BT3ziE8PGQqEQ7rrrrpLHLl++HMuXL5d2fjRIRhN5ypPZt8srN4REBZyQksdr7ZFGrju4cx0iT8b7VtaNplMV0pxgdVNVBUyb+2rVfXEMli2YjtbdpWl/br2J11QFdiXnRq6GuoPT+8idkxBO6bFO46Mhq13aRHFFkEje4fVZEbfzSt8uItmGtj7I5SxomuLq1gde4qVV2k3bdiEY0EtW0dx4roCciVRZE4iWw826yE1x/u+PbbzSvDQJkc7a99dzGh8tXVNsV5B1bfzPxr4++zRNp3G3En0/yGiXNlEYJLrAgSp2uY3M1S6Sw0s3hEQFTVMj2Pr6XgCAoijF1gdLOSElzEurtJ09KQykjZJCMOU4VxkZFrImUmVMIMpa6PFSkOi1SQhZz63psHrsND6qYzoWRhr3IaUKBXTE+0vXaUe+N6pJ9f7mLnLIlDDaO5O2424k5WJF0njphpCooH1PAvXRABL7VxJ1vTwNxAGmX3tp24Bf17AzPnh9LEwW1Avua5KVYeGliVQvTVDLInMSwku8FtDJUBf2I2ETJNaF/RU4G3dgkOgCn1n+Hty/bjv6B4x8NSUANUEdn1n+HuFjV/vNEHnrhpCooLMnVSwA4tNVZPcXDxC9eWP6tde2DchZOpGZYSFr20C5r+WyiqAosH/V3Bh8ypqE8BrH12yiT6SCfLqKgF/DQGYwdTfo1+DzQE91WRgkukS5S2YDvBmiPJk3hJyEkKfan1tZkxtMv/bWalfGMIsrykOrT2YMsatkZ08KqbRRclw3riDJupYHfVpx8mXYuF/wptgp4nAlC6ZlwTSt4iS9qjossR7E/D4VaZuWKn7f+CcMvLZSnTVMpDO5YYFxOpND1hDb7+llDBJd4OGnX0f/gFH82QLQP2Dg4adfx7wL5PQ0dOPNAMkh64aQkxDy8LmVN7nB9Os8r2wbiNWHYHanSlpKiE4W+HUVO4f0PzMMEz3xNBoi7kstk3Utrwnp6E8bw6qZaqqCcNA37mMC3tqT2JPMDAa0hSjRAnqTdjVED14y2qEE/RpS6dIAS3gSQpLeZGZM49WAQaILvLO3f0zjo8WbISqQcUPISQh5ZD23XlqdlFU6nOnX3iIvE8JhOcOFyxyyVj3rwwF09Q5AVQbjI0UB6gQDZS+tIGUNE6qqQB3xfshU2eqRU9sTkXYo4aBuGySGg+4MPdLZHDRVgWlZsKz8+1VVFGQEK8d6mTtfqSoja8Mwb4aoQEZwwEkIeWQ8t15cnZRROtxb+/G8FdjLICsTImPk0BANlBQsydik3FWavFVPOUt+XlpB8un26ZTVvA+tXOIpY0zjlRYJ+ZDoz5ZMGIRDYivrXsYg8SDmtZshkkNWcMBJCHlkPLdc+c3z0n48Lwb2MsjIhCh8xkaWt3fn95div29OcGluWKplQRlSLSfXBm0rtk+uFXtuVcV+8lykj/ysxigsCyWrtLMaI+M/qAfJWP3NZOxX4JzGK+3khYfgsWdbbcerFYPEg5iXboZIHlnBASch5JHx3HLld5BX9uMxsJdn2YLpePCJ10pWEt34/dWTTMOyBgMkC4BiAb0Jsb1SQ1MtFUWBtT9KEE219Okq6iN+xPuzMC0LqqIgWuMTXp2TkXW1bMF0dNjseXXj+0AmXVNtixjpApVuJbXhlOaM42ajY18/Xvj7HmRzJnyaig+8byrOOG52pU+tYhgkVg23fixJNlnBASch5JHx3HLl13sY2Mslo6q4DP0pA6ZpDUuCM00LyQGxFT9ZqZax+hBMC6iLBEaMu++7Zt6cyWjdHceGl3cimcoiHPLh5IWHVN11zGnF0I37SGVpbulCe2cS04f0KG/vTKK5pavq3g8FDBJdQFZ/GqYqESA3OPDKiowXlfu55cqv9zCwz3tsSys2vLwTiVQWkf038aKz+5u27Sr24Rw57rbvtIyRs71HEC2oMTTVMpezoOvlSbX00iptc0sXXtrRiWiNH9Ga/B7Pl3Z0Yva0qOveBzIZNquIBxo/GDFzo5RYx1QqC8VhqsZpfLQO9Ian6uF0YXbjBZvkmTdnMs46aS4aG0JQFQWNDSGcddLcqr34eQE/u/kA8bFnW5HozwIWkOjP4rFnW/HYllah43KVNv8+CgV0xOpDOLQxglh9CKGAXpb3l1dWaTdt24VU2kBnTwq7upLFSrLVdp8ko22JU6aqQAarVPxOKMWVRBdQVcC0mRBUBT9IfMMTwLRQGsSVX2/hZxfY8PJOmKZVUpZ+w8s7hVYTvbRK69c1h0bnYmmhstrMeGmVtq0jjh6byrFt1ZRnKUlNwId4qjQlukawD6csXvpOmCgMEl0gv2JYOl0jupLINzwVMDgg8qZq/+z2JTPDerVZFpCzLMQFG1zLTL8ud9sS3WHvoEhRkQIZbWZk9XWUIWuYyJnWsPeYpirIVlmfRBlFZhyP6dJlZW7JKMUg0QU0VYHd9nNNpK4z+IYnIiJvUxUFdjvyRCdRZa3SyqgFoCiAriklLTDKsdhV2O+ZHDAQDupl2e/p11W83TdQPF/DMJHJ5srQ17H8MlmzpGF8zrSE+2XqmgIjV/q+1bXqWaF02jPr1ub0zNwoxSDRBZy+MkQvAHzDExGRl4VDPnQPSQccOi5KxiqtjOIXPl0dXJYpRImWeBXSx7a04tFNLcVgLpvN4dFNLQAgFCgmB4xhAZIFwMxZSA64r4n6QMb+nJzGafRMhyVDkZYlslV75sZIDBJdwGm+qhwfJL7hiYjIq6bWh9CbSA+7HqoKMLUhVLmTOgAZtQDqw3509Q4MBojI/299WCxQ/vPzb9sGc39+4W2hINH5ObAfryS71b4DjVf6uF4S8uu2exJDAbHJDVVRbANQVTD7jkoxSHQBx5XECT0LeXkOfAAAIABJREFUcoNy72UhIvKy5EA2X7BmyJhlAUmbm083kFMLQIGqKFBHpioKphslHPosJgSfWyNn2d6/VFOAREDAryJuMy8Q8AnupXXqG0dlxyDRBZyX5PkpqCbsa0lEI1X7xFF3PA1NVUqqm9qloLqBjFoAGSOHmqCOeH8WpmVBVRREa3zC++akVCtBPj02nSndd+ZzKMBTSYpiX0iFxU3FpdK5knhO2T8uwqcpSNuk2vmqaL/nRHHfJ7YKZR2+6LNV1MSU2NeSiIYrTBx1dKdgWoMTR80tXZU+tQmlqgp0TYVPV6FrqqvTymT0I/XrGhL9WViWBViAZVlI9GfhF1yRcQqERAOkWY1RqKoCCyj+UVUFs6ZFhY7rtAIlsjLl1EZEtL0IAUbOtO2XaeTE7m1nT4tCVxWoyv4iTgqgqwpmC76/qBRXEl3Aa2WCSQ72tSSioWQUQfGaplgYLbtKWzM0xcLCx5a1SlvuWgDJgQyMEW1ATMtCMiXWBkRVFZg2KaCiQfjRcyfhjZ29peNzJgkdV8bCZzSk2656RkO8PRalOsw2iL6/Vh4/G/ev247+ASP/2ltAIKBh5fGzhY5LpfgpcAGn9Gr3zpWSDOxrSURDceIof0P4qydeK+m5J3pDKDO9v9BWIpHKIhLyCbeV6Oi2f72dxkUpgncf2/+5D9aIuxoLFra37BN6HpzSa0XSbtMZ+7+bFk3lpWETG8PGBfemtu6OI53NFVe8FQDpbA6tu+NlaWFTzen9IzFIdAGfT7X9kvOJbu4lqQpfJt2JDBoifuEvE/a1JKKhOHGUD9g+/y9HlL2V06ZtuzCQNhAfEnxGQz7hVdrHtrTisWdbiz8n+rPFn8cbIBkOW0+cxkfLqfpkULD6ZFtHHJY5otiQCbTtLl0RrrS0kYOqAuaQp1JV3dvLz0tMhyDRaXy0Nry8E6ZpFSseWwBgWtjw8k6hSQjWhSjFINEFnNJKmW7qXkO/THy6WpYvE/a1pKE4o0mcOMqT0cqprSM+rPiNYZjojqehCG7I2/DyTpiWVdL4XugGVlK6UV3EZxsk1gm21nCqp+DGOgsBn4Zs1iwJaP1B7kkUpesqcjapvLpgAaOeeLqkRZxpAT1xsfRrpveXYpDoAjmHWRWncao8WV8m7GtJAGc0KY8TR/I4BSwZQ2wFqS+Zse09GE+Ov61EJORDvL/070dCgsFczoKqoKQHpegimq4pyNjcv+gurD5ZF/YjYfPc1oX9FTibg0usLoD2zn7bcRFOt8aiHQGY3l+KQaILWA7veKdxqjx+mZBMnNGkAk4cyVlVd2rH4NMFV5AcM4PGfz0/dGoEr7Z2246LyBrm/uIiQ1Y9FQVZwUB59rRavLmzt6RtyezptULHlcGnq6gJ6ehPGcXnoCaki78PCOGgH7qaKnkfhEPuDMBj9SG07o6X7H+u5qqp3PTmArLKUJM8sfqQw3j17BUieTgJQZTX3NKFXz3xGppb9mHn3iSaW/bt/1msDcisxijqo4F86puST4GrjwYwq1Es8FIcKjc6jY/G7n39GPnXVSU/LsK0LBj793blK6bmi42IbnVZefwsBPwa9nfsgGUBAb+GlcfNEjuwBH49n27q01X49XyblWzWFG4vQvlV+cl1QQQDOnw+FcGAjsl1QfH+npI0TY1gX98ABtIGsoaJgbSBfX0DaBKcjPEyfgpcgH165HpsSyuuvPdZXHzHBlx577N4bEur8DGd9gRV214hkoOTEER56ze3oieezhdpsfJ7B3viaazf3Cp03GULpiMU0BGrD2H65DBi9SGEArrwd7hfV6GNiOg0VYFfYB9WXzKTX4nB4B/LglAKKwD0pwzb8eSA2HGHVp8s/ClUn3QfKx8s50xkcyaMnJlPW2RRCGGx+pBtn0S3Xse2/3Of/XiL/Xg1YJDoAlPq7D8wTuM0eoVKc4n+LGANVpoTDRSHNUxWy9MwmaiAkxBEee2dyTGNj5aMpvcA0BSLFIPCwh9NVYRWI5z6zYlmG2Wc9mUKrvRseHknVEWBrqnwaSp0TYWq5Iv3uE1PMjOYIjzkf3sFA3DKr8zZTfC4dWWuvTNh+75t35Oo9KlVDPckuoKMFrEEwPGiJFoqGRjcKxSLRdHZ6cYZUvIqFiwhmkjlu9auPH4Wfrb+74j3Z2FaFlRFQbTGJ5RqWRPS0WtTubFGsHCNLAmbiqkAkHQYr6SsYQ5Wjy0E3Yp4ASOvmVIXwN7etO34eLXvSUBRh/eiDPjVqg66vIZBogt0xzPQNaWkZHa3YDlf8tbFimgoFizxFrYskaMpFkHLrr7SccHViMJex0KRio7uFFp3x/H5fzlC+HXz+zQE/Gax+IXo1pEjmuqx4+0eJIYEnpEaH45oqhM6riyRkA99iUxJwZLaiPsKlpiWhdyIarS5nOVYQfNgdeKxh+B3z/xz2HSJsn98vF5t7R4WIAL5gNGuCJMbNMXCaNlVOuHfFAsLHbfcPbUnUkXSTf/85z/jiiuuKP68detWrFq1CmeffTbuueceAIBpmrj++uvx2c9+Fueddx7a2trG/FgvKWwaH/q/JM6pRHjYpTOwsjS3dOG+dc248YEXcN+6ZuGiD0Q0qNCypKM7BdMabFnCz5m4lcfPQsOIAjMN0YBwERRZex03bduFTDaHdCaHrGEinckhk805ViwejWULpqM+EkDT1AhmNkbRNDWC+khAOP3caZVIZPUIAN43qwG5IQVwLCvf0ut9sxqEjiuDqihQlP0Fdvb/yQe1FT6xCfb8qx22+weff7Vj3Mfsd9jb6jQ+Wk4vjehLtvL42QgFdeRMC9mciZxpIRTUsfL42eM+5tBrg2VZnrs2THiQeNNNN+GOO+6AaQ7OLqxZswZ33HEH/vu//xuvvPIKtm/fjieffBKZTAZr167FFVdcgVtvvXXMj/WKUEAv6YmYMy2EAlzoFXXyQvtZMKfxgxFvYOViAE4HallCYubNmYylC6Yj6M+vxgX9GpaWYSZe1l7H19t70ZvIwDTzpT1N00JvIoPX23vHfUxZ+yfP/8h7EQ7qQ7MsEQ7qOP8j7xU6btYwURfxQ1UVQMlnRtVF/I69KSvJtEpXDatxov6dLvtKuU7jo+G0Giv83MqKEgEEfRoCfg0+XUXAryEomAXg9WvDhEchixYtwqmnnoq1a9cCABKJBDKZDGbOnAkAWLZsGbZs2YLOzk6ccMIJAIBjjz0Wzc3NY3qslzilPopWGAOYAlXYd7jh5Z1IprIIh3w4eeEhwvsRvYQ99+Rh03sC2LJEpuaWLry0oxPRGj+iNfl0xZd2dGL2tKgrP2OO13PBLQ4y0s/nzZmMFR+cmb8+DhgIB3WcvPAQ4X+nsyeFgE9DZkjKbcCnCX8e/D7VtqiOSLuKnGEfsRg59wW0MpkOEZ3T+Gj4ddW2OJJTj9LRcgoyRYPPTdt2IRjQERyxQCNyr+T1a4O0IPGRRx7BAw88MGzs5ptvxumnn47nnnuuOJZIJBCJDO4tCIfDePvtt0vGNU0b02MNw4CuO/96sZh7mmMOZO03SA9kckLn+bcde/Dos60AAE1TsS+exqPPtqKurgaLjpw67uN6zRc/Ph9f/Ph8qf+Gm95PI3UnMrZfyj3JjKvPW6Zy/d4v/HGH7XP74o69OGXJ7LL8G5Tn5vdqU2Mtdu0tLcYwY0rE1ectWzl+d1mfsTkz6vD62z2l44fUCZ23BdiuaFhw33v4bzv2YNubXZhUG8Sk/X3ut73ZhWOObBS6RwiH/GjvTCKXs2DBgmFYyBomYpNqhJ6DSI0P+2yKq0RrfOM+rmGatlVijZwl7fWqluOesPAQPPXC27bjbjtXQM690shrQ+H4Xrk2KJY18Yvqzz33HB566CHceeedSCQS+MxnPoPHH38cAPDAAw/AMAzs2bMHxxxzDE4//XQAwIknnojHH3981I/duHHjRP9aREREREREnlfxPomRSAQ+nw9vvfUWLMvCpk2bsHjxYixatKgY6G3duhVHHHHEmB5LREREREREY+eKyig33HADrrzySuRyOSxbtgzHHHMM5s+fj2effRZnn302LMvCzTffPObHEhERERER0dhUJN2UiIiIiIiI3Kni6aZERERERETkHgwSiYiIiIiIqIhBIhERERERERW5onANAaZp4lvf+hZ27NgBv9+Pm266CbNmzar0adEBfOITn0A0mu9z09TUhFtuuaXCZ0ROXnnlFfzHf/wHfvnLX6KtrQ1XX301FEXB4YcfjjVr1kBVOV/mJkNfr+3bt+Piiy/G7NmzAQDnnHNOsd0RVV42m8U3vvEN7Ny5E5lMBl/+8pfxnve8h58xF7N7zaZNm8bPmYvlcjlcd911aGlpgaZpuOWWW2BZFj9nLmX3esXjcc99xhgkusSTTz6JTCaDtWvXYuvWrbj11lvxwx/+sNKnRQ7S6XxD31/+8pcVPhN6Nz/+8Y/x6KOPIhQKAQBuueUWXH755fjgBz+I66+/Hk899RROO+20Cp8lFYx8vV599VV88YtfxJe+9KUKnxnZefTRR1FfX4/bb78d3d3d+OQnP4n3vve9/Iy5mN1rdskll/Bz5mJ/+ctfAAAPPfQQnnvuuWKQyM+ZO9m9XsuXL/fcZ4xTDi7x0ksv4YQTTgAAHHvssWhubq7wGdGB/OMf/0AqlcKXvvQlnH/++di6dWulT4kczJw5E3fffXfx5+3bt2PJkiUAgBNPPBGbN2+u1KmRjZGvV3NzMzZs2IDPfe5z+MY3voFEIlHBs6ORPvKRj+Df//3fiz9rmsbPmMvZvWb8nLnbqaeeihtvvBEA8M4772DKlCn8nLmY3evlxc8Yg0SXSCQSiEQixZ81TYNhGBU8IzqQYDCICy64AD/96U+LvTv5ernTihUroOuDSROWZUFRFABAOBxGPB6v1KmRjZGv14IFC/D1r38dDz74IA499FD84Ac/qODZ0UjhcBiRSASJRAJf+cpXcPnll/Mz5nJ2rxk/Z+6n6zquuuoq3HjjjVixYgU/Zy438vXy4meMQaJLRCIRJJPJ4s+maQ67USJ3mTNnDj7+8Y9DURTMmTMH9fX16OzsrPRp0SgM3bORTCZRW1tbwbOhd3Paaadh3rx5xf//6quvVviMaKRdu3bh/PPPx5lnnomPfexj/Ix5wMjXjJ8zb7jtttvwpz/9Cd/85jeL214Afs7caujrtWzZMs99xhgkusSiRYuwceNGAMDWrVtxxBFHVPiM6EB+/etf49ZbbwUAdHR0IJFIIBaLVfisaDSOOuooPPfccwCAjRs3YvHixRU+IzqQCy64ANu2bQMAbNmyBUcffXSFz4iG2rt3L770pS9h9erV+PSnPw2AnzG3s3vN+Dlzt//5n//B/fffDwAIhUJQFAXz5s3j58yl7F6vSy+91HOfMcWyLKvSJ0GD1U1fe+01WJaFm2++GYcddlilT4scZDIZXHPNNXjnnXegKAquvPJKLFq0qNKnRQ7a29vxta99DQ8//DBaWlrwzW9+E9lsFnPnzsVNN90ETdMqfYo0xNDXa/v27bjxxhvh8/kwZcoU3HjjjcNS86mybrrpJvzhD3/A3Llzi2PXXnstbrrpJn7GXMruNbv88stx++2383PmUv39/bjmmmuwd+9eGIaB//f//h8OO+wwXstcyu71mj59uueuZQwSiYiIiIiIqIjppkRERERERFTEIJGIiIiIiIiKGCQSERERERFREYNEIiIiIiIiKmKQSEREREREREUMEomIiAS99tprOPLII/GnP/1p2PiWLVvw+c9/HitWrMBpp52Gr3zlK9i9e3fxvx955JEA8m0/5s2bhzPPPLPY4Hz58uW46667hh0vkUjgjDPOQHt7u/xfioiIqpZe6RMgIiLyut/85jf4yEc+grVr12LFihUAgBdffBGrV6/GPffcg2OPPRYA8OCDD+KSSy7Bb37zm5JjTJ06FevWrSv+3NHRgRUrVmDlypU47LDD8Morr+C6665Da2vrhPxORERUvbiSSEREJCCbzeL3v/89Lr/8cmzfvh1vvfUWAODee+/Fl7/85WKACACf+9zncPrppyOTybzrcTs7O2FZFsLhMADg4Ycfxpo1azB16lQ5vwgREdF+XEkkIiIS8Mwzz2DGjBmYM2cOTj31VKxduxarV6/G1q1bcfXVV5c8/oILLrA9zp49e3DmmWcinU6ju7sb8+fPxz333INp06YBAL7zne9I/T2IiIgKuJJIREQk4De/+Q3OOOMMAMDpp5+O3/72t8WVQkVRAACZTKa43/Dkk0/G3/72t5LjFNJNH3/8cZx55pmwLAtLly6duF+EiIhoPwaJRERE49TV1YW//vWv+NnPfobly5fjuuuuQ19fH/785z9j/vz5xWDQ7/dj3bp1WLduHQ499FBks1nHY6qqiq9//evo6OjAT3/604n6VYiIiIoYJBIREY3TunXr8KEPfQgbN27E008/jb/85S+4+OKL8dBDD+Gyyy7DD37wA7zyyivFx//jH//A22+/DU3TDnhcXdfx9a9/Hffeey86Oztl/xpERETDcE8iERHROP3ud7/DV7/61WFjn/vc5/CTn/wEDQ0NuPPOO/H9738fe/fuRX9/P6ZPn46rrroKixcvftdjn3jiiVi4cCH+8z//EzfddJOsX4GIiKiEYlmWVemTICIiIiIiIndguikREREREREVMUgkIiIiIiKiIgaJREREREREVMQgkYiIiIiIiIoYJBIREREREVERg0QiIiIiIiIqYpBIRERERERERQwSiYiIiIiIqIhBIhERERERERUxSCQiIiIiIqIiBolERERERERUxCCRiIiIiIiIihgkEhERERERURGDRCIiIiIiIipikEhERERERERFDBKJiIiIiIioiEEiERFRlbIsq9KnQERELqRX+gSIiIgmynnnnYfnn39+2Jiu62hoaMDSpUvxta99DY2NjQCA3/72t7jmmmvw+OOP47DDDis51sj/3t7ejg9/+MMH/Pe3b98OXR9+6R3N3wOASy+9FJdddtm7Pm60/vCHP2DDhg247bbbynZMIiI6ODBIJCKiqnL44YfjpptuKv5sGAbeeOMN3HnnnXj55Zfx+9//HoFAYNzHv/DCC3HaaafZ/reRASIATJ06FWvXri3+nM1m8fnPfx6f/vSnsWrVquL4tGnTxn1Odn784x+jtra2rMckIqKDA4NEIiKqKjU1NTj22GOHjS1evBjBYBBXXXUVnnrqKZx++unjPn5TU1PJ8Q/E7/cPe3w6nQaQDwrHchwiIqJy4Z5EIiIiAPPnzwcA7Ny5s8JncmCWZeFnP/sZVqxYgXnz5mH58uW4++67YRhG8TEDAwO48cYbcdJJJ2HevHk49dRTceeddyKbzQIATjzxRGzfvh1btmzBkUceiRdffLFSvw4REbkQVxKJiIgAvPnmmwCAmTNnCh3HNM1hAVuBXarpeNxwww145JFHcOGFF2LJkiXYvn077r77brz11lu4/fbbAQA33ngjnnzySVx99dU45JBDsHXrVnz/+9+Hpmn4yle+gvvuuw9XXHEFwuEwrrvuOrznPe8py7kREdHBgUEiERFVnaFBXDwex7Zt23Drrbfi0EMPxUknnSR07G9/+9v49re/XTL+1FNPoampSejY//znP/HQQw/hsssuwyWXXAIAWLp0KSZNmoRrr70W559/PubPn48XXngBCxYswCc/+UkAwJIlSxAIBFBXVwcAOOqooxAKhRCJRJjSSkREJRgkEhFRVXnllVdw9NFHDxtTFAXHHnssvv3tbyMYDBbHRmPk4/7t3/7NtnDN1KlTx3nGg7Zs2QLLsvDhD394WKC7fPlyAMCmTZswf/58fOhDH8LatWtx7rnnYvny5Tj55JPxhS98QfjfJyKi6sAgkYiIqsoRRxyBm2++GUA+wPP7/Zg2bVpJpc9QKAQAxX18I2UyGQBAOBweNj59+vTi/sZy6+7uBgCceeaZtv+9o6MDAHDddddhxowZePTRR3H77bfj9ttvx+GHH45rr70Wxx13nJRzIyKigweDRCIiqiqhUGhUQdyUKVMA5AOv9773vSX/fffu3fD5fGhoaCj7OTqJRqMAgJ///OfF/z/UpEmTAOQrpl588cW4+OKL0dHRgY0bN+K+++7DpZdeis2bNwu1+CAiooMfq5sSERHZmD9/PmpqavD444+X/LdcLocnn3wSCxcuhN/vn7Bz+uAHPwgA2Lt3L+bPn1/84/P5cMcdd6C1tRW5XA4f//jH8d3vfhcA0NjYiFWrVuHcc89FIpFAX18fAEDTtAk7byIi8hauJBIREdkIBAL46le/iu985zvIZrNYuXIl6urqsHv3bqxduxY7d+4spq1OlPe+97342Mc+hm9961t45513cMwxx2DXrl246667YJom3ve+90HTNCxatAi/+MUvUF9fX3zMAw88gCVLliAWiwEAamtr8frrr+N///d/cdRRR5Wk2xIRUfVikEhEROTg/PPPx4wZM/Dggw/i2muvRSKRwKRJk7BkyRJcf/31OPzwwyf8nG699Vb85Cc/we9+9zvcc889qK+vx4c+9CFcfvnlxXTTb3zjG6itrcXDDz+Mu+++G7W1tTjllFNwxRVXFI/zr//6r7juuutw4YUX4rvf/S5OP/30Cf9diIjInRTLsqxKnwQRERERERG5A/ckEhERERERUVFFgsRXXnkF5513HgCgra0N55xzDs4991ysWbMGpmkCAO655x58+tOfxtlnn41t27aN+bFEREREREQ0dhMeJP74xz/Gddddh3Q6DQC45ZZbcPnll+O//uu/YFkWnnrqKWzfvh3PP/88HnnkEXzve9/DDTfcMObHEhERERER0dhNeJA4c+ZM3H333cWft2/fjiVLlgAATjzxRGzevBkvvfQSli1bBkVRMGPGDORyOezbt29MjyUiIiIiIqKxm/DqpitWrEB7e3vxZ8uyoCgKACAcDiMejyORSKC+vr74mML4WB5bqPDmxDBy0HV39Ig655uPIzVgIGcO1hDSVAU1QR3/dSOrzRERUXX62vefgV19PVVVcMe/n1SBM5p43/3li9i1N1EyPmNKBKvPW1yBM6qMs65+DJlsrmQ84NPw61vPqMAZTbwzV6/D/p1Ww6gqsO72M8d93E+sfnTYPWiBpir4n9s/Pq5jfu37zyCZyqIvmUE2Z8KnqagN+xGp8Ql9dq/5wSa8/nZPyfjhh9bjlkuWjfu43/3li9j+z73oS2aQMy1oqoLasB/z5k6pqs/ZUBVvgaGqg4uZyWQStbW1iEQiSCaTw8aj0eiYHvtuurv7y/QbiLNsPpgAYJoWOjvjE3w2NFaxWJSvk4fw9fIevmbeU67XrCHiR0d3qmS8sSFUNe+J9o4+2N0mvN0RL9tz4IXPWNYoDRABIGPkXH/u5eLUj8CyIPQcODU6sKzx34c2RPzIZHOYXBccNl4f9guda8s7vcgauWGfCVXJj4sc9wNHTsFbu/sQrfEPG1985JSyvL/c/BmLxezjpopXNz3qqKPw3HPPAQA2btyIxYsXY9GiRdi0aRNM08Q777wD0zQxadKkMT3WS0IBrWQGJ2daCAXcsdJJRERUCcsWTB/TuBs0t3ThvnXNuPGBF3DfumY0t3QJHS9WH3IYD9qOH6y0/Zlkox2vtHK/DwAAkprW+XT7cMBpfDSWLZiOVNpAZ08Ku7qS6OxJIZU2hD+7mWyuZNLEtGC7yjwW8+ZMxlknzUVjQwiqoqCxIYSzTpqLeXMmCx3Xyyq+knjVVVfhm9/8Jr73ve9h7ty5WLFiBTRNw+LFi/HZz34Wpmni+uuvH/NjvSSdsckdAJDO2o8TERFVg8IN2qZtu9DZM4BYfRDLFkx37Y1bc0sXfvPMP4s/d3Snij+P95yXLZg+7JhDx6tJfTSAvb0DtuNuI+N9AABQICVQjNUH0d5ZmmEnOhGRyeaQzuRgWhZyOQt+gaCzwOnXL8fTMm/OZNd+t1RCRYLEpqYmPPzwwwCAOXPm4Fe/+lXJYy677DJcdtllw8bG8lgvSWUM+/G02KwIERGR13npxm3Ttl2O4+P9HbwWKMsSrfGhL5lBxhicQPfrakl6oBvIeB8AB043FeO0Gjv+Vdr1m9vQP2BAUxVo+4/TP2Bg/ZY2oefAdEyNHfchyUHFVxIJB5gW4TueiIjIKzp7SvdP5sdLV8DGwkuBsixZw0TWMIeFLfkx902od/akMJA2EE9lYeRM6JqKaMgn/D5wWkgUTbi1W6E90PhotHeWFlsCgPY99uOjpasqMjbVezTVnWnHXsYg0QUUVYHdrnSFb3giIiLPiNWHbAvtVNv+weaWrv0rnynE6kNlWfnsTWZsA6TeZEbouDL4dQ1tvfFiJdJM1sRAxsDhgqmxigpYNjuRFMEszrTDfj6n8Ury+7Rhq8lDx6m8Kl64hvLpEiNnQDRVKUvuNhEREU0MLxbaKbfCfryO7hRMa3A/nmjhlv4B+605TuOV1NWXKmlVYZpAV6/9SvNoaar9faHT+GjJSGNtioWRMy1kDLP4J2daaIqFx39QAH6fWrJyquwfp/LiSqILNMUiaNnVB01VoChKsRRx09RIhc+MiN6NjBlzIvIm7h+UuR/PuU2D23TH7Vc3ncZHS1MVZB3G3WZKfQg73u4dNpYzLUxxqNY7WsmBbMmKsgUgWYbJgse2tGLDyzuRSGURCflw8sJDcMZxs4WP61UMEl1g5fGz8OATryGeyiJnWsXc9ZXHzar0qRHRAUirYEdEnlXt+wdl7ct03pDnvgDJqbiK0/ho+TQVaexPAR3yfIi0qpDl723d0DUFpmnBQv50VVXB39u6hY6bcaj8L9oC47EtrXjs2dbiz4n+bPHnag0U3feuqkLz5kzG0gXTEfTn86mDfg1Lq2zmkciLDjRjTkRUjWL1IfQm0mjfk8BbHXG070mgN5EW3pcZDvocxt233qEWI4ghAAAgAElEQVQ6BK5O46NVE9KhaUoxLlYUQNMU1Dg8N5WUSGWhKgp0TYVPU6FrKlRFQTJltxY6erIqvG54eeeYxqsBg0QXaG7pwrPbdmEgkwMsYCCTw7PbdpWn8SoRSSNtxpyIyKN8uoreRAamaQEWYJoWehMZ4dWugENhEqfxSlId0j+dxkdrVmMU4ZAPyv4oUVEUhEM+zGp03/akSMgH07Rg5PJVaY2cCdO0EA65L6AF8kGtHdGg1ssYJLrA+s1t6I6nYeyv1mQYJrrjaazf0lbhMyOiA4k57K2otkqGREQFf2/rhqoqsIDin3KkGTrdxDuNV5JfVzGyloyqQrggYdPUCJKpbHEfpmVZSKaywjUsnBY4RRY+3zerATnTKq7wWVZ+T+L7ZjWM/6AAnOJs0W2ZEYfg1a1B7URgkOgCsnrJEJFcrGRIRDRcXzK/iqgAxT+maaEvKRbMOe05E92LJkNTLAwVClRl/148BVChCFf23P7PffbjLfbjo+UUIDmNj0bWMFEX8edXT5X8REFdxI+sTfuKsXBcUfaLrSifvPCQMY1XA/clchNR1fNKxVBWMiQiGk5VFORsKsy4sACnNEfPnYw33+lDsWIL8v979Fyxa0N7ZwKWNdha2wKgWOKLCqd94FA8+tcWmFZ+5U9R8q/jaR84dNzH7OxJIeDTkPHnU011TUXApwlvx8jkHArXCAafheI0G17eiWQqizCrmzJIdIOmWBivt/cWP/RA/st0zvRo5U6KqEK8VjG02isZEhENVRPS0WvT6kE0bc/v0/K1G2zG3aZ9TwKRkA/x/nxqqKIoiIR8wsFcodfgUIVehCJkBEh+XcPOeLL4c2ErVX00IHSuZs6hcqzD+Ficcdzsqg4KR2KQ6AJ2vWRMC8K9ZIi8SFaPLSIiku+Ipnq89nYP4v1ZmJYFVVEQrfHh8KY6oePOaozizXd6S1oqzJrmvgn1to444v3ZYkCXsyzE+7N4q0MsSLRM+0DIaXwsyh8gWTAtq+T1Ei1D6vS33dct0/sYJLqArF4yRF7EiqFERBOjkNrfncigIeIvS7r8sgXT0dGdQl0kUDIuYmhP6UL6olt7SvclM7Yrfr3JtNBxZQZI5d7m0ZPM5IPEIamxsCz0Cu5NdWyXKXRUssMg0QUSqWzpO96q7rK7VL1i9SF0dJcGiqwYSkRe4JU91c0tXcWgK5ezsFNT0LY7js/9yxFC5ytrr3ahp3Q+JdIsW09pGa9X2iYt9kDjo6WpSknwWRgXIWObR3/KgDkiC9Y0geSA2L2t6vAciLYXoVIMEl0g4NOQyO7/0Oxfic9ZFkIubBBLJNuyBdOHXayGjhMRuZmX9lSv39yGrr6BwSwmI18pdP2WtrIEdOX+fZtbuvD0S+3FNFYjkcHTL7Vj9rTouP8tWa+XU/anaFZoTUhHxma/Z43gfk8Z2zwGMob9eNp+fLRqAjriNosoNbxnLju2wHCBurB/TONEB7N5cybjrJPmorEhBFVR0NgQwlknzXXdDRYR0UgHutl2m7aOOHK5EX3schbadscre2IOHn76DfQm8u01YOXbavQmMnj46TfGfUwvvV4AoDuslgm2X0RnTwqptIHOnhR2dSWH/Dz+bR6yAuWA3/6XDfgY0pQbw24X8OkqakI6+lNGvvQw8rNFPt19FbuIJgIrhhKRF3lpT7VTvzrRPnay7OrqH9P4aMh6vWTtm+vqs9/T6DQ+Wn5dxdu9A8UWGIZhIpPJoSEy/sUKn64iZ5Ne6xOMaFNp+5Rdp3EaPwaJLuDXNaQzOSj7vz0U5PPW/ZwVISKiKueVPX6At/ZU65qCjM2yjq65c2+XZVm2gZclUC1T1uulOBTxVASfWqdfVbBgKJIDBowh74V8L0YLyYHxp4ZGQj7bliURwdTYdNZhv6fDeKXJKA41URiFuEByIGOb8pFMleadExERVYvCnrGO7hRMa3DPWHNLV6VPzZbT3mk37qmePS0KTVUGJ6iVfAGU2S5sKQHk6zfYjvvHn3W1bMF02zRL0ddLxrnK1Nlrv3LqND4asoK5nEM/RKfxShr6/WVZluu/v0ZikOgC3fGM7Rd1t83mZCIiomrhtT1jXtpTvfL42ZhUF0QwoMOvawgGdEyqC2Ll8bMrfWq2JtfZr+5NrhVc9XuXn8dDdViN1VR33nYbhgkFKPljCKQep7M5jNxCqSr54kgi3BcKOvPa99dITDd1CVVVoEKBoihCqRNEdHDwUoodkSxe2uNX4JU91fPmTMbn/+UIbNq2Cz3JDOrD7k6F8+kqwoX6DShP/YZN23YhGNARDOgl4yLPQ8qhgmd/2p2tzXRdtW3PIbJ/MODTkMkODzJNC/A7rLKOll9XkbEJXkX3OgLlv+568ftrKHdOaVSZpljEfnyq/TgRHdy8lmJHJEusPuQw7r49fl7mhblpv64hmzXh01X4dRU+XUU2awrVb5B1Ez+yP+C7jVdarC5gOz7FYXw0HFNuBYPED7xvqu2q5wfeN1XouDKuu17//mKQ6AIrj5+FhmgAuq4CSn5GpyEawMrjZlX61IioAryeokJULl7a4+c13tsvZeX7I+ZMZHMmjJwJ07KEIlyv3cRrDi0wnMZHKxz0Q1cVqEo+4FKVfLuNcGj81U1TaaPkvDRVcVxlHa0LVh6F4+dPy68cKvkVxOPnT8MFK48SOq6M667Xv7+YbuoC8+ZMxuc8lPJBRHJ5PUWFqFwK18F8CtgAYvVBXh/LREYDdZl6kvkeiYUinBYAmBZ6kuNP4Vy2YDp+9cRrSKSyMHImdE1FJOQTvokPBTTblgyhgGCqpU+1Pa5oNfyMkcPkuiDiQ56HaMhXki46VpqqCAewdhon1SBS40MilUUk5EPjpBrhY8q47g79/upJZtDY4K2tIwwSXcYLKR9EJJeXyugTyeaVPX5e47XJqP4Bo6QRu2kB/QNi+/xkFK6J1YfwVkfCdlyE3V48QLy3ZeGaM3Jvpsg1pykWRsuuuO24iMe2tOKxZ1uLPyf6s8Wfzzhu9riPK+u6W/j+isWi6OwsfT7cjOmmLtDc0oUHn3gNzS378NbuOJpb9u3/2a0pH0Qkk9dTVIjI/byWamnXc+9A46NRKFwTqw9h+uQwYvUhBAO6cGr/zs7kmMZHy6nNgyHY/mHZgukYGNEKZECwFcjK42cjFNSRMy1kcyZypoVQUBeunrvh5Z1jGh8tXndLMUh0gfWb29AdTxdLDRuGie54Guu3tFX4zIioErxURp+IvMlrN8W5nP1qmdP4aMhaTc2NXPJ8l3E3SGdzSGdyyBom0plcWZrTB30aAn4NPl1FwK8hKFi0BgASKfuV46TD+GjxuluK6aYu0N5ZmpIAAO177MeJ6ODHFDsib/JK+xqZ+6VkPAdO4ZVI2MXU/rz1m9uQ6M/mW7BZgAULif4s1m9pG/frJqu9SCTkQ088PSz1WFWA+uj4K7EW8Lo7HINEl8hvxraKvX9UpfwbfYmo/LxyQ0hE8hUqhhYUKoYCcOX3goz9Ul56DpYtmD7sXIeOV5PW3X3DVjktC8hZFlp39Y37mJ09KaTSRklRINFV2kjIh3196WFjppUfp/JiuqkLNET9yJlWsWiNZeVTEhqi4y89TETysZ8hEQ3F9jXyngPFYfLcaXw0ZKUYOp2SW+f/nfY0iux19Osqegpbqaz8VqqeeBp+XexJ2N3VP6ZxGj+uJLpAOOiHovTnl873fx5VBUL9aYhIPq+VkCciubxWMbSQCdGdyKAhUp72W7KeA5+mIG2zp8+nlSvyKt9+waDfvgVG0C+2J8+nq7aVTH262JqPT1dtCwCJHVdOpOxU4dVpnMaPQaIL7OlJ2ZZ13mOTJ09E7uG1G0IikstLe9yGpoX6dLVsaaGynoNYfRDtnaWrRSLHbW7pwn3rtiM1YMAC0LorX2H+4jOPFnoOasN+ZLIDw1I4NVVBbVhs31xjg/1z0Ngg9txOqQui3aby6pS68R83Y+RQE9QR78/CtCyoioJojXjvRQX24Xw5pgq4fWQ4V6Sb/va3v8V5552H8847D5/5zGcwf/58PPHEEzj11FOL488//zxM08T111+Pz372szjvvPPQ1pav/rl161asWrUKZ599Nu65554K/zZjl0xloSD/BlcUFP+/aKUmIpLLayXkiUguL1UMlZUWKus5CAf90DUFqpK/V1IVQNcUoayrX/zxH+jfHyAC+eCjf8DAL/74D6FzndUYxeS6IGqCOvw+FTVBHZPrgpjVGBE6row2IHnlLwvk1zX0DxjQVAU+TYWmKugfMOD3iYUeMgoYAdw+YscVK4mf+tSn8KlPfQoAcMMNN+Css87C9u3bsXr1aqxYsaL4uCeeeAKZTAZr167F1q1bceutt+KHP/wh1qxZg7vvvhuHHnooLrroImzfvh1HH310pX6dMTMt+7e25TBORO7AogdENNTQiqGdPQOI1QdduxohKxNC1nOQMXKYXBtEfEghlGhIbGWqqzc9pvHRWrZgOjq6UwiNqOwpem3YF8+MaXy0uh3+vtP46Djcw7r03nbTtl22hXaqefuIK4LEgv/7v//DG2+8gTVr1uDCCy/E3//+dzzwwANYsGABrrzySrz00ks44YQTAADHHnssmpubkUgkkMlkMHPmTADAsmXLsGXLFk8FibVhP/oSmcHqpkq+umk0zD2JRG7mpRtCIpoYXimjLzM1VsZzUDjfkS0VRM5X1qqUrGuD6dBn0Wl8tFIZY0zjo5ExTOi6WkzlVQCEgjoyhjuDxLaOOHrig5MDhUI7bW6tNjQBXBUk3n///bjkkksAAEuXLsWpp56KpqYmrFmzBg899BASiQQikcGlek3TSsbC4TDefvvtd/23GhpqoOviTT3LYeWyuXj4z69h5NmsXDYXsVi0IudEY8PXyVvK+XqdEovilCWzy3Y8ssfPmPfwNSufv+3Ygyeffwu7u5KYNjmMU5fMxKIjpwodc+UJh+GXj79a/LlQpGTlCYe58rUbeb5Dx8d7vj5NRTZnXwhG9Dmo25dCIOCDrmcQCPhQV1cjfExVQUkNi8K4yLFNh8VY0xz/cU0LSKUNQBncL5hKGzAtS9r7S+S4OdO+Uq5plu98/z977x4dWVnlf3/PpW6pqu6qTlfSbadJ0o7NALEFBIQmCA4Cjq2itg444rxoOwyOMss1ggg6oMAA4nLWb5YOlzVLZ/h5x1FfkKw19hpm9WBflH6b7mnTYoN0Ejohl+p0JamqVNWpc3n/OKlKJXVOqNRTT3Kerv1ZKwtqkzw8da7Pfvbe3+3F+2opPOMkzszM4MSJE7j00ksBADt37sSaNWsAAFdffTV+9atfIRqNIpudL6w1TRORSGSBLZvNlv9uKVIp70jlvmvbRpw4mcLBlyZQNEz4FBkXn9OGd23b2LC+RQQ/GtlfiuAPnS/xoHMmHnTOGsfivoOvjc3gu8/0Y5qxVcPmdSF84PIu7D06iqmshljYVjfdvC7kyXO3eV0I297cij2HR5DJFREJ+XDVBZuY5nvJuW3Y97uxavs5bUzHgNc5UxXZUcVTVWVu56zecU9P5x0zS0/P5D03VwBQZOcyL0WWGjJfLz8T3ZxXTwjXAMDBgwexfft2APZJ+sAHPoCxMfvGLaWPXnjhhXj++ecB2GI1W7duRSQSgc/nw2uvvQbLsrB3715cdNFFq/Y96qF/YBLDySw2rg/jzZvWYuP6MIaTWc8Wy9pqYP24/8mDePzpfs/OkyAIgiBEZyV6L3q0TGwB/QOTOHQ8iWiLHxtbw4i2+HHoeJJpDbJrx7m4/K0b4FdlSJLd2+/yt27Arh3nMs2V1zlz06qwGNNNeeCawurQGmQ5yC6ei5u9Vjrbo4hHA1BVGZBsxzseDeAsRrEhkfFMJHFgYAAdHR0A7HDvAw88gM997nMIBoN485vfjL/4i7+AoijYt28fbrzxRliWhQcffBCALXZz++23wzAM9Pb24m1ve9tqfpVlU1ksaxgWFEXybLHs4t2xRklmEwRBEARRDS+BGV4tMHjBqy/trh3nMjuFi+F1ztx62zP0vOeHa8En22TXhP2YchDUWcvYXqR320YMji2M9FlobiE6zziJn/70pxd87u3tRW9vb9Xv3XfffVW2888/H0899RS3ufGmslhWkiRPF8tS83CCIAiCWDl4CczwfJ/z6DcnUl/aRCyEwbF0lVJm1wbGmjROzqAsSY5K+7LMsA51+1PGpe3Wjhj+94+nUKhQtQ34ZLylYy3bwKiemvdW4SuLZ9JNm5miQ365bWfte9N4RHpIEwRBEITo8Oo7mJzKIV/QkZzK4eR4puJzYyKUje43J1Jf2o62CCan85jN69CKJmbzOian8+hoY0td9Ln0GCyJDjV6XD/DuG4BQ9bUZp8qQyua8/3FAWhFk/kY7D06imBARSIWwsbWMBKxEIIBtaFp3aJBTqIH8KkyTMuCbpjQdAO6YcK0LPg9or5aiUgPaYIgCIIQnZ7uVuy8cgva4yHIkoT2eAg7GQVQALvZeSpdgD63Ua3rJlLpAnOz871HR8vO5+hktux8si62eTnLPHjh9+MwFtUJGqaFF34/zjRuV3sEi5PMJMm2s5BY67yGW+9irwW3KCRTdBLAS0MpQLKDqqUfSHN2BigIUo1n0k2bmVg4gMnp6otwbcR7fRKpeThBEARBrCx8ei/yCfUMjaeRnM6V2ypoRRN5TXdsL7AcROpLOzo565iqODrJpqyvKHLV6bEs285COKhClhe2wpBl214vQb/imCkX9LMFQKYyBcdjMJ0pOP9BjfDsGyoq5CR6Ak4xeQ6I9JAmCIIgCMIZTTcRiwbKonmqatfNsTY7n8loVX33TBOYzrIt4gFeznLjsSzLcWXnpk5aK38cnl6WvVamshpkSIBkwbLs6KQMCVPZYt1jtgRVZHLFBUtZSQJagj6mufJaMlMQpBpyEj3AVFarvugtYJrh5uSJKA9pgiAIgjgT4CEEk4iFYKZyCAVU+FS5HPVhjZwUis56CgWNXWeBx3HgwVL9DFlwGhNw17aolaJuQpYl21FcYK//nPlcop4+hVUORoKzp9g8keqVgpxED1B5c0qSVN5p0jwoXEMQBEEQxMrRPzCJH+x+Gek5pczxVA5DY2l8/NqtTAtY0SInIrXgUhQJcGgTqDDW48kS4NQSkVUM3030hUUbYzqjObpt09nq9hXLQXLxERvREICCIAsh4RoP4HZz+jwoXEMQBEEQxMrRt39oXmDGmheY6TswxDTuAkEcuXGCOOGgb4HyZOknHGJLMyz1lK4UxMk1QBCHB+6q9Ww5ka7qpj629WJnexQtQRWGaaFomDBMCy1BlamRfEE3oCiS7bxJthOnKBI0l0hzrSwWBHojO1E/FEn0AJ3tUVgWquoCOhnVqgiCIAiCEJvhZMbZPuFsXw6lyEkiEUUymX7jP6iBay7ZjGf2DsA07bo8Cbai5TUXb2Yat7KnNABP95SWJQmSQ7iLMZAIv6KggGoHlKVVBWC37DjyyikosgRlLv43m9eZWnZEQj5kZouQF6WXsm4WECsHOYkeoHfbRow71AV4NeWDIAiCIAjCifdd1gUA2HN4BNlcEeGQD1ddsKlsr5eibrcHW+x8erGndEtIxXS6Oq2S1UHK5p21KrI5Ng2L4YkM4tFAOaVZVWREQz6mjYirLtjkuFlw1QWbmOZKrBzkJHqAymLZqayG9rh3i7EJgiAIglg5OhJhDIxWR/k6EuFVmE1tvO+yLmancDGWBRjGfHTOgv3Zg0Lw2NoRw8snp5CeLcK0LMiShGiLD2/pWMs0rltGJWumZXIqh0LRQEEzYFoWDMOCX5WZegR2bYgiEvIhPVuEZVmQJAmRkA9dG6JskyVWDKpJ9BhefNgRBEEQBLE67NjehVg0YCtjSrZCZiwawI7tXas9tRWlVNO2uMbNg9mmrplgXs0QK+ompjMaTNMCLMA0LUxnNKYo7d6jo/D7FAT8CnyqjIBfgd+nMNeQyi4n3M1O1A9FEj1ApWKXT5U9rdhFEARBEMTK0dPdipuu3cpFmr/UUiKV0RCP+D2dxcRL5I9HW43BsfRcj0B759+yLGRyRQyOpZnGVhUJulEdTVAZ20pMZ5wVR1mUSIfG05iczpcFZbSiiYJmQGJ05lRFcuzlyXoMiGrISfQAJcWuknCNotgh+b1HRz37sCYIgiAIYmXgIc0v2gZ1LOxHcipXTq20AMCyEAvXX+fXPzCJ7+9+GZmK9iKDY2ncxNheZM/hEVc7SxpuOKg69tAOB9mW8yUl0sX1gyxKpDNZrUpx1DAtzGQLLn9RG36f4tgv0s+o8EpUQ+mmHqCk2KXPXfRlxa5xduUygiAIgiCIxbil/XmxpQQAZPM6LHNhWw3LtO310rd/EKdn8sgXdBR1E/mCjtMzefTtH2Sa60xWg25YMC27jMi0AN2wMOPg4C2H9Kzz37vZayUS8tmiQBXzNS2LSWinUHRuA+JmrxW3eCFlmzYechI9gHs/He8pdhEEQRAEIT7JqZyLvX6xEp6k0gXIst1YovQjyxJS6fojU4PjmXnxG2teHIffJj2b8AQv4ZoN61pgLlqKmqZtrxfLRWTDzV4rmm449uFk7b9IVENOogfwqTJMy4JumNB0A7phyzz7GfPsCYIgCIIgnEjEQi724ArPpDZ0025/UekYmKYFncFD0nVzgdNZ+nHbvK8Vt7o71no8Xoydnq3q4ShLtr1eFJfv6mavFVWxXZfK81VpJxoHHVEPEAsHHO1rI/4VnglBEARBEM2AaAqcbg3jWRrJyy7d7d3steJXZciLpiXL7E3vfarzvNxEfWplJqvBshal8lpgSo8NBpzrJN3staLMRZMrsebsRGMh4RpPYPfQkRUJkiTNh+KpHwZBEARBEBzg2aP52QOD2HN4BJlcEZGQD1ddsIm5b2JLUEUur8O07PRQSbLbHoSD9dfNBf2KY9Qw6GfL5OpIRPDHkWlUppdKkNDRFmEaN+hTUdSrHTfW+cqSBN0hFZbF73ILGLIGU2cLzjWobnaifshJ9ACabiIWDZTVTVVVRiTkc5T4JQiCIAiCaAQl1dREIopkMt2QMZ89MIhn9w2WP2dmi+XPLI5iZ3sUBc2wm7Njrjl7iw9ntdfveLUEVWRzxQU1fbIEtDA4ngCwPhbE8ZNTC2yGaWH9WrZU3rxL3V1eY6vH46EY6jQewJ7K69QCZCk7UT+UbuoBErEQQgEViVgIm9sjFZ+9WRdAEARBEAThxFLtH1joaItgNq9DkSX4FBmKLGE2rzNF52JhP2RZgiyVIpN2qilLWw0AOPrq5LLstWK61F+62WvFMJwdN2Oxms1y4CRcQ6wc5CR6ANHqAgiCIAiCIJzI5Jzr2LIu9loZnsggHg1AVWVAAlRVRjwawPAEixKpBFmSoCoyfIoMVZEhSxJzTqTbd2U9BrwUQwsuEcoCQ4RycY/EN7IT3oPSTT0Az7oAgiAIgiCIlSIS8iHj0LePpeceYLfsCAbUKuETlpYdmm4gHg0gnStCN0yoioxoyAeNsZefmxvE6h7xaoHBY1xKCxUfchI9Ao+6AIIgCIIgiJXkqgs2LahJrLSzkIiFMJ6q7u3IUppTGnOx48la7iPB2SH0qv6mJDlnh3qxY4cso6qnY8lONBZyEj1C/8Ak9h4dRSqjIR7xUySRIAiCIAjhKInT7Dk8gmyuiHCD1E17t23ED3a/XBX1YynN6d22ET/7nxOOdhZ4Rfx4IUsSDAcvUWbwEnk5yn96Vhy/H0w52onGQk6iB+gfmCw/pHyqjPFUrvyZHEWCIAiCIHjAa4P6fZd1MTuFTjj1x2OhstwnOZVHIhZsyk36tRE/pjPagnpBRZaY+nWHQz7H+lTWtOOJ1Oyy7ET9kJPoAfYeHXW1N9uDiiAIgiAqKTkyyakcEjGq2W8Uom1Q81orlcp9GolI6ZvAfIrw4ob0LCnC53bFcfTVyQXtOYJ+Bed2sUX8Tk0XlmUn6oecRA+QnKrOsbft9RdjEwRBEIToVDoyADzvyIgEzw1qHo790HgaU+l5R0DXTUylCxjyoOclQYLlEOeUPDhXgE+KcEdbBC8eT0Kec5glyT5nLC1LiJWFnEQPwKMYmyAIgiBEhzJt+MFrg5qXY+/WhL2oszWS54GiSDD1aidxcaTOSzQ6RfjYicn5wsTS15ZsO49UZKLxkJPoAXgVThMEQRCEyFCmDT94bVDvPTqKXEFHpkJgJhLyMTv2PlWGaVkwTavsd8iyBL+qMM2XR9STVz9DVZEcW0ioivecz+FkFrIkQV40t+FkdpVmRCwXchI9APVJJAiCIIhqeGbaNHutI68Nal5pobFwAJPT1ZsDLOIqvKKevHoEyrIEOIwhezhCSYgLOYkegfokEgRBEMRCeDkyVOvIb4OaX1qo5RiZclSIqRHR0pm1ovOxdbMvh0ZvmnQkIhgYnam2U02iMJCTSBAEQRCEJ+HVokA054AXPDaofaoM07RgWlZZsESW2NNCNd1ELBqoSmPVHGr/aoXSmW36Bybx/d0vl4/teCqHwbE0brp2a933w47tnY59LXdc1sk0V179F3khch90zziJH/zgBxGNRgEAHR0duOGGG/CP//iPUBQFvb29+NznPgfTNPHVr34Vx48fh9/vxwMPPIDOzk4cOXKk6ncJgiAIghAfHi0KklM5x7q5ZnQOGr2AjYX9dlroIsGStWG2/niJWAizYwsdWQlsqcckHGjTt38Qp6fzZcde101omoG+/YN1Xw893a24fNvGOcVUE0G/gssb4SAJ5CWK1mZmMZ5wEgsFO3f9e9/7Xtl2/fXX41vf+hY2b96MW265BceOHcPIyAg0TcNPfvITHDlyBA8//DAee+wx3HvvvVW/e955563W16kLkXcaCIIgCEIk/KqMEYe6uThDfZto8FvASs5poYw1iR1tERx55VT5s66bSKULuJwh9ZiEA20Gx/ogTH0AACAASURBVNLQzXnPy7IA07IwOFZ/dLl/YBL7jo4irxmwAOQ1A/uOjqJrQ5Tp+hLIRxQ+Y8ETTuIf/vAH5HI5fOpTn4Ku67jtttugaRrOOussAEBvby8OHDiAZDKJK664AgBw/vnno7+/H5lMxvF3RXISK8P8hmFhRJGYw/wEQRAEQbjhsqT0aB87Huw9Oop8QUd6bu2hKBKiDVAh1XQD8WigKs2QtW5ueCLjmG46PJGpe8ye7lYMjqWx5/AIMrkiInP9AZtt7eVeR1r/OevbP4TUoo2YVLqAvgNDTMc3HPQhkytW20NskWqg8XWZoqcze8JJDAaD2LVrFz760Y9icHAQf/3Xf401a9aU/3s4HMbJkyeRyWQQicwXvCqKUmUr/e4bEY+3QGXMj28Uu5/6X0xntPJnw7AwndGw++Aw3nVJ1+pNjKiZRCK62lMglgGdL/GgcyYeXj5nJoD1sRBmshqKhgmfImNN2A8L3p53Ixk5lcXUorXHVEaDemqW6Rh0tK/B6KkMouGFUdk3rY8wjZvKaNANE1rRgGHarTB0v4KprFb3uC8en8DRVyexbk0Q69bYKaZHX53E285ux4Vnt9U916XgdX15bdyRySws2NeVBQsSJCiKhNdPZZnm+sF3/Ql+vPt41bgfvOpPmMZ98fgEntk3CABQFBmn0wU8s28Qa9e21H0tlO6FEj5VBsB+L6wUnnASu7u70dnZCUmS0N3djWg0iqmpqfJ/z2azWLNmDfL5PLLZ+f4qpmkiEokssJV+941IpWYb+yUYGHh9utw7R5Kk8r8PvD5NSqcCQIq0YkHnSzzonImH189ZPOKHVjTQunZh7Vks7Pf0vBtJrqA7rj1yhSLTMbj47PX42Vi1quVFZ69nGjeXL+L0TEVkyrBweqaAloBa97h9v37VMVrW9+tXsXldqO65LgWv64tlXDfpH4th3KJuLji2FiyYugVFlpjm+q5tG3HiZAoHX5pA0bCgKhIuPqcN79q2kWlcHtdC5b3gU+Xy+Kz3QqNxc1jlFZ6HI//xH/+Bhx9+GAAwPj6OXC6HlpYWvPbaa7AsC3v37sVFF12ECy+8EM8//zwA4MiRI9i6dSsikQh8Pl/V7xIEQRAEQTjhVnPWTLVopahGtZ0ty6qnuxU7r9yC9ngIsiShPR7Cziu3MKdwTs44p+i52WtB9HTARuGWZM2SfO3mYLBmdPcPTOKV4WmoqgyfKkNVZbwyPI3+gUmmcXlcCwvuBblx98JK4YlI4kc+8hHcdddd+NjHPgZJkvDggw9ClmXcfvvtMAwDvb29eNvb3oa3vvWt2LdvH2688UZYloUHH3wQAPC1r32t6ndFgnrJEARBEMTKwau1hkh0tkdhWSjrIaiqXePX2c6+9uChSFvQnPssutlrgdRNbZaKJNaL6dK/0jRZRp1TYp3JwzQtWJhTYi2yKbEC/K8Fhnaeq4YnnES/349vfvObVfannnpqwWdZlnHfffdV/d75559f9bsiUdlLxjCthvWSIQiCIAjijWjs6q3R4he86N220VG90qvRVEmSHFfaEkNoSjR104BPRsFBACjgY0sMdHNgWBwbVbHTKyt9Qlmy7SwMjmegGxVKrABMw8LgeP0CRoB9zp36OrJcC9QCg2Cmp7sVH792K/YeHcVUVkMsTC0wCIIgCIIXlYs3AA1bvPEalxfSon/xsrZrPOrHqemCo71eKtVNs7kiwh5XN3V15lZ2GjURj/oxm9cXXFOWxXa+AKDoopLLosRaYvFxZD2u1AKDaAil1AyvF/sTfBFlB5ogCEJkeC3eRFoULpirtdDutbkCQOuaIE6nCzArfAFZtu310j8wiUPHk4i2+BFtsZ2XQ8eTzL38eKG5OEKs7UVkCXDKApUZdg3CQT9kOQejYmBFlhAOsTmJlovrZjHmc+49Olq1SSKB7X4QveaVnESC8Aii7UATBEGICq/Fm0iLwqHxdLmPnSRJ5T52LOmbPNF0E2ta/EjPFmFaFmRJQrTFB02v3zmo7BVZmWLoVUeZF3/aGcfvB1OO9nqZyhYgSbajacF2uCQJC1q+1QOP1Fhg4f0AoCH3g+g1r+QkeoRSBCmV0RCPULppMyLSDjRBEITI8Fq8ibQodEvP0/T6hWB44lcVzOZ1KLIEZS7mM5vX0b6u/ho3Ho6BiLznHWfhlZNTKFbU+vkUCe95x1l1jyna9cVjvqLVvC7GEy0wmp1SBGk8lYNlWeUIEqucLyEWIu1AEwRBiAyvFhgitdbg1QKDH40PIfFyZPwuQjJu9tWmb/8gLNhRv8roX9/+wbrHNC3LbnhvAbDs02QYlmNaqxfgcT9QCwyCmb1HR5Er6GUZakWREGnCdIdmR6QdaIIgCJHh1QJDpNYane1RFDRjLn3TLKdvNqIFBg803UQsGkCmIjU0EmJLN+XlKPtU2bFO0KsO+OB4BsYixVDDsDDEoBgqSxKkRbWOssRW58iTypYwldcX6/0gsuYIOYkeYGg8vaDni6QDWtFounSHZkf0tASCIAge8BL04tHLbyEeDZnM0dEWwYsvJ8uCH5ZlIZMrNqRH87MHBrHn8AgyuSIic4qh77usi2nMRCyErEPLDpaNVF6OQS6vu9iLTOPyQneJqLIohppWddTQtLzbL7B320aMp3IIBdQqe7NCTqIHmM3p8zs40nxIftajDxOCDyLtQBMEQawEogl6iTTfYydOO2r+Hxs4zeTQPXtgEM/uGyx/zswWy59Zxu1oi+DIK6fKn3XdxFS6gA6GRTyvXpFuKZVeTbVUVRkFrTrFVnWJtNaC4RLh1Q32VhU8oDVYNeQkeoCiYc4/pyvuqUb0fCHEgv/ONkEQhDiIJugl0nyHkxnIsgQZEiRJKkcUhyfYmpLvOTziamdxEocnMohHA1VKpKzzdWp70Gwk1gYwnJx1tNdL0cUZ9PLaltZgCyEn0QO4bSx5dMOJG9QjkCAIgqhENEEvXvMV6f2YyRVhmFZVf7xsji07KjmVQzCgIrgoHZDl2O49Ouo4phedep6Eg36ocg6mZQvN2OI1bD0NaW0rPuQkegC/KkMrhfkllO8gP0OYXzREStEhCIIgVoZELIShsXRV9KhzQ3S1p+YIDwEyXu/HjkQYA6PVqZYdiXDdYwK2Q7hYtMUwLWZlz0QshGMDpzGb18t991qCKs7rXlf3mKJtQvBC0w0oqgRdK9WnAj5f9XlcDgvWtovshBjQmfIALUEV0pzcsGXNNR2VgHDQt9pTWzGWStEhCKIx9A9M4vGn+3H/kwfx+NP91GaH8DwdbRGk0gVbWMOa72PXCHEVHvBogcHr/bhjexdCQRWGaUHTDRimhVBQxY7tXUzj8iKTKyI75yAC9lopm7eV4eslEQu52JtLVTw9q6GgLXQIC5qJ9GzB5S/emJagautsYP4HTba2FR1yEj2AT5EdFaBUpXky42k3jyD4UtmP1bRA/VgJIRieyCAWDdgCGpItpBGLBpjr0HjR092Kt5+dQHpWw+hkFulZDW8/O8EU8eP5fgz6FAT8Cvxz/wz62Fs0uNWcuSlo1sofh6eXZa+F3m0bkS/oSE7lMDqZRXIqh3xB96yipZvoPasYfiqtLcteCz5FrlIytZpsbSs65CR6gOms803oZj8Tod08guALResJEUlO2ZL0iVgIG1vDSMRCCAVUz24g9g9M4tDxJKItfmxsDSPa4seh40mmzRhe78dSPV4iFsLmtggSsRCCAZX9mdD4nvcAbCEUCaj6cRNIqRUHgVdmFJdmgG72WomGnKNwbvZaMVxkV93stTB2uloIZyk74T3ISfQAWZdWF7MufXbORHik6BAEMQ9F6wkREW0DkcdmDK/3I69nguTiCLnZa8WnuDS+d7HXwt6jo46bEKyOMg+nC1hCMdSDbSV0w/m7utlrhVc0laiGhGs8gOlyb7M+TESC+tMQBF94CGoQBG96t21cINpSaWeFh2IoD8eL1/uR1zPBr8owHdRNWQVLLj6nDft+N+Zor5fkVA65gl3XWBJGioR8nt08yxeqhWCWsp+JuEWkWSPVgFgqwisBOYmEZ6D+NATBD56LbYLgRU93KwbH0thzeATZXBHhkA9XXbCJ+V3BSzGUl+PF4/3I65nQkYhgYHSmKrWSVWyofV1LpQA8ADvdtH1dS91j+lUZI+l5cRZdNzGVLiAeqb/1A09Eaishy85BENmjOYyksl+NR08VQRAE0Uh6ulux88otaI+HIEsS2uMh7LxyS9O+/AgxqKzx29CgGj+AX42uSKUTlSI7JycyDRHZAYAd2zvRMqeaWjRMGKaFlqCKHZd1Mo275/AIfKoMf8WPT5Wx5/AIw6iUuwjAtT0JS9uSjoTzpoCbfbWhuv1qKJJIEERTUEojSWU0xCP+pkwjoWg9IRpLLdy8qBhaGfnM5IqINCjyyYNKB3zdmiCKuolDx5Po2hD15HzdWl1kGVpgaLqBeDRQ1YeTpT8gYPuYTumPrL4nr3Hj0QDGT1ffE+ui9UfAU2nn9hlu9tWG6varoUgiQRBnPJXtHyzLovYPBCEIvBZuvARxeKib8oJX5KRv/xBm8zoUWYJPkaHIEmbzOvoODDGNG3FR8AwzKHuWFF0rhWvsz2zXgeoipuNmrxWfS12nm73mcV3nW7/3mZ51dt7d7KuNaCJZKwE5iR6Al1QyQRA2lEZCEGLCa+HGKy1UpGcNLwd8OJmBaVnQDRNFw4RumDAti7m35VUXbFqWvRZ4XQeqy/qNtUcgr/XidEacVmy81E1FShVfKSjd1AO0BFSkHdIlWoJ0egiiEVAaCUGICS9xFV6KobyeNTxUF3mJ7OimBaOizYEFwDAsGAqbvMr7LuvC+OlZHHxpAkXDhE+RcfE5bXjfZV11j8lLGKmgO6uNFopsKqRuqvcmoxp+TnNuuZbzoGpqwKcgr1XPK+BTmMbl9UwQudSFvBAPsDbid3QS14a9qa5FEKJB7R8IQkx4tkfiUaPL41nDS3Wxd9tGfH/3y8jkijAMC4oiIRLyMTvgflWG5rCIZ02J7B+YxLGB02VHyTAtHBs4jf6BybqPQ2kBn9cMWADymoG9R0eZ6zLdWpu52WtFcQmXydwyz7ynm6q79IR0s9dHY7535b3rU2XhFFPJSfQAmbxzfnYm77yzQxDE8qD2DwQhLiIJLvF41vAS7wEArWigoBkwLQuywd7LELCzoHJ5HaZlwbLsNEBZktASrL92EACe+u8/YqoiLdKwLExlNDz1339Ez676jkPf/kFMObTA6Ns/6M1rjpMvyLP3YKOpjFLXYq+V/oFJ/GD3y2URo/FUDkNjaXz82q11Xws8792VgJxEDzDjkvM9k/WmAhRBiEZlNGIqq6E9Tk1yCYJoPDwin7xSWPv2DyIzW4Q15wlYloXMbJHZQepsj6KgGUjPFmHBgiRJiLT40NnO1vpg5FR2WfZaGE46/62bfbUxTMuxVyRruqlI/Rd5zbVv/xBOTefLkWqtaKKgGeg7MFT3/SB6qQs5iR6AV1oCQRDzlKIRiUQUyWR6tadDEMQZSqMjn7zS5QfH0tDNhbWDpmVhcIzt+djRFsGLx5O282kBFmzns6ONzUnkFe0yLQumacGC7XDxS91kR5ElLA4rWGCfs5uTyep88mCxk1xpZ+HE6ExVzadhWjjx+kzdY4pe6kLqpgRRJ/0Dk3j86X78/f/5Hzz+dL8nJc4JgiAIseGluljUnXei3ey1cuzE5JzDiQX/PHbCe+/IeDQAw7DTYmHZDqdhWIhHA6s9NUfc+jey9nUUCcmlLlNidJR53A+iK6ZSJNED8GqOSvBD9GJkgiAIQgx4iffwStsbHM/AnEuLLGGaFgbH2Vpg8CAcVKEoUlUkMexRdXk3dVM3+5mI5XKFWh4soFygnpvXEQ6qDVHPXSkokugBRCoYJmxE6oVFEARBnCk0bmHgGpFh3KHWXSIvbvbVRNNNrFsTRDCgwqfKCAZUrFsThKbTAsyr8Foz8+i/2D8wiUPHk4i2+LG5LYJoix+HjieFyTwjJ5Eg6kD0YmSCIAhCDEqZK+OpHExrvgUG60KTV2N21UUhlbUFBg8SsZCLXYyasUbhdso9XJ7ZcNyuT5brVvSAgvfu2CaEx+4FwRd6sRAEQRArAa+FpuriAagK2+Kjqz0CWZYwV+ZXFlZhVTflQUdbBKen88gXdBSLJvIFHaen88wiO6LBK6osEjwilKIHFMhJ9ACyW3PUJro5RYNXMXJJDOf+Jw+SGA5BEATBbaGpu9Sx6Yz95s7b0mrX9klY8M/ztnivDuvYicl5WcyKf3pRZIcnposn5GavhVBAWZZ9teGh8Cp6QMETlbnFYhF33303RkZGoGkaPvOZz2DDhg249dZb0dXVBQD42Mc+hve+97349re/jT179kBVVdx9993Ytm0bhoaG8KUvfQmSJOEtb3kL7r33XsiyOP4vFSLb9A9MzhXm55CIebuPHY++e5ViOABIDIcgCILgJqPPq+3B8EQGkRZfVZ/E4QnvCdcMJ7PzZZ4l5RrLu30SeSFJkqPwC0sk8c8v7cQv/udEVU/HP7+0s+4xAWBNiw8zs0VHOwuqKsPQjCo7S7pp77aNC9Z1lXYR8IST+MwzzyAWi+Eb3/gGUqkUPvShD+Gzn/0sPvnJT+JTn/pU+feOHTuGF154AT/96U8xOjqK2267DT/72c/w0EMP4fOf/zze8Y534J577sFzzz2Ha665ZhW/EbFcRHSQGt13b6mUIq8eA4IgCIIvvBaaqirDLC2KK5rPsdYODo2nMZvXocgSlLnw3Gxex2seVDfVDXNhr0jLjp4phvdEdngiS4DTN2apSRw/PVsls2TN2VnIFvRl2WslsTaA4WT13Navrb8dCo+AwkriCSfxPe95D6677rryZ0VR0N/fj4GBATz33HPo7OzE3XffjUOHDqG3txeSJOFNb3oTDMPA6dOncezYMVxyySUAgHe+853Yt2+fUE6iqkiO6R2sdQEiwdNBEiVCKXruOkEQBA9EeYaXaPR8ebXA6GqP4NXXZ+bbP0iNqR106yun6dVRmuXgU2XHsVmcWl5tQETDLXjMElT+7bFxV/uuHefWPa7hkg7tZq+VcNAPWZpd8J1lCQiH/EzjNjqgsJJ4wkkMh8MAgEwmg7/7u7/D5z//eWiaho9+9KPo6enBY489hn/5l39BNBpFLBZb8HfpdBqWZZVD4iXbGxGPt0BVvZEXfeWFHXju4ElHeyIRXYUZrTypjOb4oJ/KakzH4MXjE3hm3yAAQFFknE4X8My+Qaxd24ILz26re9zFNOI8dbSvweip6p3WN62PNM11sFLQ8RQPOmfi0YhztlLP8EbBa77vSkTxrku6GjPJOf7yz8/FP//4RcxkNRimBVmWsCbsx1/++blM5y4YUJHNVUd1QgGVadyzz4qj36FW8OzOeN3jLuVw8HrmNMu4rjWvpjePbTpfhKLIgGHZadKQoCgSMrliw+Yr2nvME04iAIyOjuKzn/0s/vIv/xLvf//7MTMzgzVr1gAArrnmGtx///24+uqrkc3O54lns1lEo9EF9YfZbLb8d0uRSrGFuxtJPl+dW12yi7brUC/xiN+x5qI9HmI6Bn2/ftVx57Hv169i8zrnguLl0qjdoYvPXo+fjc1U2S86e33TXAcrgYi7ec0OnTPxaNQ56/v1q5jJasjkitANE6oiIxLyNfQZ3kh4vXN4RFOnp2ftKOLcWt6y7HrE6elZpnPXsT4MXTerztmm9WGmcU3TOUJpGmbd47o1YLcsi2mukuSsiilJ4PYsYxk3oMrIOdTjBXwyl/l68RjkCzoklLL45jP5cgW9IfP18nvMzXn1hLrLqVOn8KlPfQp33HEHPvKRjwAAdu3ahaNHjwIADhw4gPPOOw8XXngh9u7dC9M08frrr8M0Taxbtw7nnnsufvvb3wIAnn/+eVx00UWr9l3q4cCxsWXZz0R4qYWKlMLZ092KnVduQXs8BFmS0B4PYeeVWzydVkUQBMGTofE0ptIFuxG7ZTdkn0oXMOTB+jbAfufkCjqSUzmMTmYrPtf/zuHVJ7Fv/1C5dtCvKlBkCbN5HX0HhpjG7d220Y4axkLY2BpGIhZCKKAyv89fPjm1LHstBHzOGWUBP1ummao4L6/d7KsNjx6BouH2Xf0eyTpcDTwRSXz88ccxMzODRx99FI8++igA4Etf+hIefPBB+Hw+rF+/Hvfffz8ikQguuugi3HDDDTBNE/fccw8A4M4778Q//MM/4J/+6Z+wZcuWBfWNIuCyOeZqXw6i1HLwqrngpQoHzB/bVEZDPOJvyHxLuesEQRCEe31bkbG+jRd+VcZIulD+XHJq45H665r2Hh1FvqAjXRGZi4Z8zDX7w8kMdNNcsNaQZTCrkPJ6n7u15mBp2REOqY4RtHCQbXlsuCzg3OyrTTbvIgbjkDZ8ptLZHkVBM5CeLcK0LMiShGiLD2d5sL/nSuEJJ/ErX/kKvvKVr1TZf/zjH1fZbrvtNtx2220LbN3d3fj+97/PbX6iIppiKA8HiZcqXOWx9amy548tQRCEiIi3u+8iOMfQSmBoPI3UIsczlS4wNzrXdLNqM9o0bXvj8LYETNqhlcJS9lrhufnPA5FasfESe+xoi+DIK6eqVHk72prXSWyeOHITspRiaLPQ092Kt5+dQHpWw9hkFulZDW8/O8HsyNGxJQiC4E9nexTxaACqKgOS3bYhHg14dndf0w20BFUYpoWiYcIwLbQEVWjF+r0DXmqhhkubBzd7rfBKj+WBblgoVaBV/rBEJwm+uG2OsG6aDE9kEFv0rIlFA57s77lSeCKSSPBBpHo8XvQPTOLQ8SSiLX5EW+x0n0PHk+jaEGVyFOnYEgRB8Kd320aMp3IIBtQquxfxq7Jjj8D2eP0LWPd6MbZoKo+2B4C9WZor6FXCNV7s+etTZRQa3ECd4IvpcoG62WuF1nXV0F1wBpOIOSupNaIeTxR4Rfzo2BIEQfBHPEGvxqebdrZHHSMcrP0MeSGS2FBnexSKItmnR7JPk6JI6NwgVqsCL+L3uaSKu9hrxe1WYgwkwq/KOD2dR76go1g0kS/oOD2dh19tnp7li6FI4hkMr3o8keC1M0THliAIYmUQSdBL0w3Eo4EqkRmWdNNSNDXU4GiqLDvXyMmM4QORxIZ2bO/Ed/teQnq2WO65HQn5sOOyztWemvC8b3sX/t/nT1Q1p3/f9i6mcU2XtiVu9lrJ5vUFNZiWBRiW5Srq0wyQk3gGw0thTCR4qZv2dLdicCyNPYdHkM3rCAdVXHXBpqY6tgRBzCOKkrSIiHRsS++cxemxLO8cXu/yloAPmVy1QEtLwMc0rk+VYZoWTMvuwShJgCxJnhUb8vsUBPxm2an3u7TFIJbH+y7rAgB7nZQrIhzy4aoLNpXt9cJLFCiVLkBRJLt3KOycAFmWFohGNRvkJJ7hiLQDywOe6qalWsd1a4Io6mZDah0JghAP0ZSkRaJ/YBLf3/1yub5tPJXD4FgaN1271ZPHln+WSeMEVVyFaxhX27GwH8k50Rqg1FTewtowm/PJg71HRxEKqFVRWi/WT4pI14Yo/mTT2vIGT5fH03hlSYLMqJJ6JkFOInFGw2sHdqlaR3qxEERzQc8DfvTtH8SUQ9/Bvv2Dnjy2PN45vDYhCi5poQWG1FgAmJwpVInfmJZt9xrJqZyjyE4zi5U0iv6BSTzxzDHM5nRYAAZH0zg2eBp/84HzPHnvdiQiGBidqbY3cQsMchKJMx4e0VRSwSIIogQ9D/gxnMwuy74ceKWxNvqdw2sTwnKp4XKz14pbep4X0/b8qowRh02IeMS/irM6M/i//3kc2dx8PZ8FIJvT8X//8zge+cz21ZuYC5X1qaZlQZYkRFuauz6VnESCqINELIShsTTSuSIMw4KiSIiGfKSIRhBNSCIWwuBYuioa4fXUqmZGpBRhXpsQsiTBcHAIZUaZSF7CInzgJJVJ4NS08/XpZvcCVJ+6EGqB4QFUl/xnNzux+nS0RZAqSXzD3n1MpQtNnZZAEM1KR1vEUfKfngfsdCScjyHrseXVHokHiVgIuYKO5FQOo5PZcookqwCbLDuvMdzsNePmC3rQRyyp0Va2F4lHA0xqtISYlOpTE7EQNraGkYiFEAqonnwmrBQUSfQAqiJDN6qloVWF3YcXSRVOJIYnMohFA8jMRRJV1Y4cDE94rw8UQRB8GZ7IOLY9oOcBOzu2d+IHu1+uOrasKWAipQh3tEVw5JVT5c/lTQhGMRy/KsMwzKoWBX7WRvISnB1CD+57l7IAKrFAPY+bEapPrYYiiR7AvacQ205WKZ1mfE5lrJRO0z8wyTQuYT9MSjtOm9sj5R2nZn6YEESzkpyyWx5U7kAH6XnQEHq6W3H5to0I+hVIAIJ+BZc3YLMzEQu52L3nHAxPZNASVGGYFoqGCcO00BJUmTch4lG/o8BMPMpWj+eWVerFbNOOtghOTeUwm9ehFU3M5nWcmso1XRYAZbTZmyNOGSF+tXmOwWIokugBjMVP6Tew1wqvYneKTvLrv0gQhHjQ84Afle2Goi2289KIdkM8W1U0+h05NJ7GbF6HIktQ5sJxs3kdQ+OskWq3xW/zLIqfP/K6o6P8/JHXmfv5iYRhuKxDXey1oCiS49971/Gk+tTFUCTxDIZHOg1FJ23cFhKN64VFEIQo0POAH3uPjiK/qB4vX9CZ64R6ulux88otaI+HIEsS2uMh7LxyC/OGJ493pHu2UXWZynJIpQuQF60CZZldhdTn4gS42VcTEcVVeMCjjFThVfPKCapPrYYiiR6AV/o+j91t6gdmU9kLayqroT3enBFVgiD49WMl7Cja5EwepmnBgp0CphUNSA3d3W9cHmTJqV1cQ8nyjvSpMkzTgmlZsCw7sCFLEvwqm/KibpgwF61/TdO2s7DlTWvxyvBUVa3jlk1rmcYlxMLNufKq01VaMwcD6iJ7pJPvmwAAIABJREFU82aEkJPoAXgJgfFIpxGp2J83pV5YiUQUyWT6jf+AIIgzFh79WAlgNqdDr0hZswCYhoVsvsg0Lq8WGEPj6QWRuJLyNYtTGwv7MTmdt798aRgJWBv21T0m4N7qgjXSY/ebm6V+c4RQ8ExBFxVKNz2D4ZFOw0uKmyAIgiAWM1vQne15Z3ut8GqB4ZYaqjGlhkqQJQmqIsOnyFAV2XbwGKOpuovugc5Qh0YQotLT3YqORBijp7J4bTyN0VNZdCTCTb35R5HEM5xG727zkuImCIIgiMWYLo6Mm71WeGXF+FzaR/gYUkNLtVKLU1hZ0/bc0kpZ00379g8hM1uEZVmABViwkJktou/AUFMvuAlv8+yBQRx8aQIA4JtrQXfwpQm0r2tpKhGjSiiS6AHcNgO9KKhU6ge2uLCX+oERBEEQjYZXOQavFhid7VHEFr0jY9EAOtvrb6lQaqmyuMUK61x5taoYHJuBblowrbn0YMuOWg6OzrANTAiFSGtbANhzeGRZ9mbgDSOJpmnixRdfxPj4OCRJQltbG7Zt2wa/n62PDjGPQH1ny/3AFhf2NmNNIkEQRAlqDcQHVZYc0yJVxro5XvVHvds2Yjxl99Ft1Lii1UoVXdJV3ezEmYlI/TIBIJNzrnPOutibgSWdxBdffBF33XUX3vSmN2H9+vWwLAunTp3C0NAQHnzwQVx22WUrNc8zGresGcZsGi5QPzAxoQUsP+jY8qN0bFMZDfGI37PHlpcICgEEA6rj4m3xRuVy4aVIy2NcUs8lCP5EQj5kZqufNeEQm0CUyCz5lL3nnnvwxBNPoKura4F9aGgIn/vc5/DLX/6S59wIDyLajiZhL2C/v/tlZObqWcZTOQyOpXHTtVtpkcEIOQf8qDy2PlX29LGl1kD88PtkKAUJRsWuqSJL8PvYq2X4K9I2bqdXLPVcXknCBMGPqy7YhKd/PVD1rLnqgk2rOKvVZUkn0TCMKgcRADZv3mwXJBNNR093KwbH0thzeATZXBHhkA9XXbBJoJdX89G3fxBTiyTZp9IF9O0fpPPGCDkH/BDp2IrYGkiUCLhPlaHIUlVjbtYegQCfY8Br40iU8wWgqvfiG9lXE5HKfQj+WIuuhsWfm40lncSrrroKt956K9773vcikUhAkiQkk0n88pe/xDvf+c6VmiPBQKNfLP0Dkzh0PIloix/RFrsu9dDxJLo2RD37wmp2hpPZZdmJ2hHRORAFkY6taGn4ImUXdLZHAQtVyp5nMQjBAPycub1HRzGVKSBT0SMw0uJj2tzoH5jED3a/XD4G46kchsbS+LgHz5doUMyTKLHn8AhkSIBkwbJsgR0ZEvYcHmladdMlncQ777wTv/rVr7Bnzx5MTEzAsixs2LABH/7wh/Ge97xnpeZI1AmPl6BIu/sEf0Ta3eaBaM6BSPA8to2+bkVLwxcpu6AkBLO4BpH12PJ6l708PIXpjFb+bFgWpjMaXh6ernvMvv1DmJzJwzTtuIaum9CKBrWUIIgGMpPVFohkWRZgWhbSWW2JvzqzWdJJtCwL1113Ha677jqkUim8+OKL8Pl8uOiii1ZqfgQDPF6CIu3uEzYdiQgGHKTHO9q8uRMvEqI5ByLB69jyuG5FExYRKbuA17Hl9S5LZ52VEFkWmkPj6QUN7i0ApmFhaCxd95gEQSzErfeqwagiKYoAmxNLVn5/+MMfBgAcPHgQ73//+/Hzn/8cP/rRj7Bjxw4cPHhwRSZI1E9yKodcQUdyKofRyWzF5/pfgrx6SxH82LG907G35Y7LOpnGXWoTolno6W7Fziu3oD0egixJaI+HsPPKLQ15AfQPTOLxp/tx/5MH8fjT/egfmGzAjMVhwbGVG3ds+V+3lKjGj8YdW17vMrcFJctCUysay7ITBLF8eKQelzYlx1M5WJZV3pQU5X1ek4b0N7/5Tfzrv/4rzjnnHADAiRMn8PnPfx7PPPMM18kRbPhVGScdUlTikfp7XFLkRDx6ulvx8Wu3CrMTLxo8VAdFi9I+e2AQew6PIJMrIjInZtWIGo7SsU0kokgmGxM1SU7lkC/oVTVuLNetaOeLV3YBD/oHJvGdvpfKNX6vjWdw/OQUdu04hzlFuLLOr3Qd0LuMIJoTHn0dRS/RqslJLBaL2Lp1a/nzli1bSN1UALJ5HcaiFBXDsJDN63WPyTOtitdCk+DjyCRiIQyOpcviF6oiIxLyoWtDlHnsZr8WRHqxPHtgEM/uGyx/zswWy59ZzxmPNB2/qmAkPZ9WqesmUukCYtFA3WOKdL4AO7vAyUFizS7gwVP//QpmKmr8TMvCTEbDU//9Cnp2sR3bxasYr65qZFmC6dCIXpZJg5MgGoUkOTuEEsNtVrkpaRgWFEVi3pRcSZZ0El977TV8+tOfhmVZeOKJJ/C3f/u3OHnyJL773e+iu7t7peZI1EkqXYAsV/eXSlUIFtQDD4eD50KTFyLlmfMQmOloi+DFl5NVkWrWnXgRr4VGI1KUds/hEVc7y/ni1yex8dvFpVT+xRsmXjxfAL/sAqDxz8XRSed7wc1eK3uPjiIUUBFaJIjjRcferVbKzU4QxPIJ+hXkCtUp3EF//e12KjclJUlqyKbkSrKkk/jb3/4Wx48fx+9+9ztIc670iy++iGAwiAcffHBFJkjUj25aME1rQb8f07SYi3B5wGuhyQteC1geETReqXDHTpx2tg+cZpqzaNcCD0RSTc3knIU6si72WuEVndN0E7FooMqh0/T6n4t+VcaIg1ooS2o/b3inSTfqueiWtcSazZScymE6U0C6olVFtMUHmSVswAm3V7YHX+XCIUvOx9GL1wHBl4CLkxjw15R06QKHHNYVZMlvrqoqzj33XHR2diISsWsVrr/+elx//fVIJpNlG+FN/KqMglZ9wfvUJfWK3hAeUSleC02Aj+PFYwHLK4LGa7E9nMxAliTIysKX6fBEpu4xAb7Xgij0btuIJ54+htm8Dgt2Y+eWoIqdV25hGpfHvRsJ+TCVKSxolC3LQCzCtlPKK5qaiIVgpnJVESQ2B9xlQdlkC00ez5pw0Of4TAiHfHWNV6Kom5ha1KpiKqMhwjguIRbuDrgYi3iicciSVJVyKkn2RkK9VG5KGoYFVWXflFxJlnQSf/Ob3+D222+Hpmk455xz8Mgjj6C9vR0AcMstt+AXv/jFikyyFkzTxFe/+lUcP34cfr8fDzzwADo7vVdfsZIoivOVrSj1O4n9A5P4p5/8b/nzwGgaL7w0gb+/4W1Mi81IyIfTM9VpsOvWsC00nz0wiJ9XRNFOFwvlzyyOV3Iq5yg/zrL7uOfwCDTddLR7ba4lnObLugnB61r41MP/XWX77pf+jGlMXuP+9vfjC2qHLdg1xr/9/ThTQ24e9+6GdS1V58s0bTsLiVgIL7w0UWW/5Jw2pnF7t21ccBxKsDjgmm443gtasdq2XES6bnk8a665ZPOCZ3jZfvHmuscEgMkZ580GNztBEGc2WtGsCvBZFttzPBELYaDyPVYEZvM6LjmHXbthJVhyNffII4/ge9/7Hn7zm9/g8ssvx0033YSJCfvLek245r/+67+gaRp+8pOf4Atf+AIefvjh1Z7SqjOVdu7LNMVQk+i0uFrKXitOTsFS9lpxWlwsZa+VgVFnpUUnxcBa4XUMeMwVgKsAEoswEsDnODgtiJeyr/a4+343tix7LfC6d38/mFqWvVacHMSl7LXC4zjwusdEu255HAdez3CntLKl7ARBnNm4ZTG52WuB13tspVgykmiaZlmg5pZbboHf78euXbvwox/9qFyj6BUOHTqEK664AgBw/vnno7+/f5VnRBAEQRAEQRAEIR5LOonr16/HD3/4Q7z//e9HNBrFzTffjImJCXzyk5/E9PT0Ss2xJjKZzIIaSUVRoOs6VNX5K8bjLVDV+hWLVopEgk9Imse4Is1VtHFFmqto44o0V17jijRX0cYVaa6ijSvSXHmNK9JcRRtXpLmKNq5Ic+U1Lq+5NpIlncSHHnoIjzzyCBKJBK655hoAwBe/+EX8+7//Ox599NEVmWCtRCIRZLPzva9M03R1EAEglZpdiWkx06gG0isxrkhzFW1ckeYq2rgizZXXuCLNVbRxRZqraOOKNFde44o0V9HGFWmuoo0r0lx5jctrrvXg5rAuWZOYSCTwjW98o+wglrj55pvxwgsvNG52DeDCCy/E888/DwA4cuQItm7dusozIgiCIAiCIAiCEI8lncQ//OEPuP766/GOd7wDX/7yl5HJzEvbf+hDH+I+ueVwzTXXwO/348Ybb8RDDz2Eu+66a7WntOp0JMLLstfC2ZtjzvaznO218vc3vG1Z9loJB52jyW72WnFTAWRRB3RTbWRVc+Q17tmb1y7Lvprj8rpueR1bka4vXvcuj2MA8Jlv90bnXdjujWvqHhPgdwxEOraqi/686qLeXSuKy7hudoIgiOUSdWmpE20Ro9XOkivlr371q7jrrrtw9tln45//+Z/xV3/1V/je976HcDjsOXVTWZZx3333rfY0PEU4qEJVJJimVe61JssSk4O0Y3snpnYXkK5oRB0N+bDjMrZ2Iz3drfj7G94218Mtj0Qs2JAebgAcj0EjKC2oEoloQ9IGOtoiOPLKKUc7C73bNjo2Zu/dtpFp3B3bu5Da/XJVU/Id27s8OK4F/1xrDkmS5p9fjM8xXscWaEybg0p4zZXnvdvoewzgM99ELOTYb42t96JNo6+DEvPHYL5nJiuVx3YqqyEW9jMf29ZYEOOnq6/b1rUhlqlCVSQYDieN1fkkCIIooahum1xsrcJWiiW9hXw+j0svvRSA7TB+/etfx2c+8xl85zvfWZHJEWxouolwyIfMbBGWZUGSJIQZm3j2dLfi49du5bIgnKdxGxDxaAAjyflaVQuAYViIr2PruceD4YlMuelqpXPE2py+dG4afc56ultxE4droae7Fb3bNmLP4RFkcyaCfoV5XF4NbXkdWx7wnGtPdyuX79w/MIm9R0eRymiIR9gdjhKNnm/vto34mUNLhkY4XjzoH5jE9ys2YsZTOQyOpXHTtVsbcv/2dLc2zLHvbI/CslD1XOxsZ9s8c+vdyLqJ6FNlFDn0jyUIgi+S5LxvzNLMQZYkyLLdO7hsk9nGXEmWdBIjkQief/55XHHFFZAkCXfeeSe+8IUv4LbbbkMuV72zR3gLvyojl9ehyBIU2FdkLq/DH2e7OnksCPsHJhcsssZTufJnlv9XOKhCaXA0tUSjF7DJqRxCARWhgLrIzt7cmdcinte1cOh4EtEWP6ItfgDAoeNJdG2I1v3/SsRCMFP28a1cxDUi0sPr2PJApLlWPhN8qtywZwIPRNosAIC+/YML+uXquompdAF9+wc9N+febRsxOFbtbLI64G7tsVmTpII+xdFJDPrrV1PnsXglbHyKhKJRfXB9FFFuOhZkGS2y14tpWbBMe+0JCYAFWCYcM0+8yJJbW1/72tfw+OOP4+mnny7bHnnkEWzevBnDw8PcJ0ew4nJhe/DNsvfo6LLstaLpJtatCSI45xwEAyrWrQkyR5BKC9jxVA6WZZUXsP0Dk3WPmYg5p081wpERCR7XgtuC0quRHoLfM4EXPd2tuPX6HvzD/3MRbr2+x3POViXDFdkVtdhXG61ooKAZKOomCpoBrcje8F6Vpar6Q8XBtlxaQioWDyFLQEuw/hqkgM/ZwXSzE7WjOziIS9mJMxfLxXNzs9eCLNnPlNKyW5Ls54wopc9LOolvfvOb8cMf/hAf/OAHyzZFUfDlL38Zv/71r7lPjmBD0w3EowGoqgxIgKrKiEcD0Ipue6irR3LKOTLNGkVLxEIIBVQkYiFsbA1XfGZzvMiR4QePa6GnuxU7r9yC9ngIsiyhPR7Cziu3eHoh3+zweiYQYtG3fxAzsxoM04JlAYZpYWZWQ9/+QaZx49EATNOCBJR/TNNCPMpWiuBTpKoogWkBLP5cxEX8ws1O1I7b8p9cxOaDx7XglmbuF6BPO/AG6aajo6N44IEHMDo6ine/+934m7/5GyiK/cXuuusuPPHEEysySaI+ErEQxlM5BBelL3oxMlWaa7Wdba68aoV4OTKAOClrvOB1LTS6VorgC6/rgAA6EhEMjM5U2xlFsnhwYjS9oJ4HsOt7Toyy3cO8ShEmpwvO9hlney1kc0Vne97ZvtoosrMoECnHEl7Gr8rQHFLF/Qz1xLGwH5PT+YWepgSsDYuxwbPkN7/77rvxZ3/2Z7jvvvtw9OhR3HrrrdB1HQAwPj6+IhMk6kekyBSvufZ0t+LtZyeQntUwNplFelbD289OMDteiVgI+YKO5FQOJ8czSE7lkC/oDXFkRElZ44VI1y3BD7oO+LFje6djlgmrSjVgp+I//nQ//v7//A8ef7qfKQUfgGN931L2WuFVilBwSYUtaPWnyOZd/jZfYE+75cG6Nc7RWDc7QXiBi89pW5BZUPq5mKlNlARZkqAqMvyqAlWRbdEsD5Z9ObGkkzg1NYWdO3eip6cHjz32GKLRKO64446VmhvBSKWDNNpAB4kHC9IBpcalA/YPTGLf0VHkNQMW7JftvqOjzAuXjrYIUukC9LmFiq6bSKULntyJFw1e1wIhFpQizI+SSnVP9zpsWh9BT/e6uc/sz9tG12rzIhELVVXtS2hEpLrxWgCipUSmXKKmbvbVxC0dkNRom49dO87FOV1xWygK9i17Tlccu3acW/eYIpV9ObFkXoWqqnjllVfwlre8BZIk4etf/zo+/elP45577oFheHMHi5iHh0okT3goL/btH0JqkYpfKl1A34Ehpv9XZbuKypYKrO0qiMV4dRlErAQipQiX1I4r+w568Tlbgsfzdqlaba8di8V9aUvvhssZI9UBv4ycQ4Qv4Kvf6RBN3VR3Efpws68ma8M+nHJIERYlHZBoHP0Dk8jmdWxuj5Zt2byO/oFJJmX1UtlXo5XVV4Iln1pf+tKXcOutt+LZZ58FAPh8Pjz22GM4deoU/vjHP67IBIn6EU0dkAfDSWenjdWZK7WrSMRC2NweKQvikKgGO5XRCNOCp6MRBAHwvWZL6Zv3P3mwIembPOFRq+3mB7H6R6WNvsod/lg0wPxuCLi0ugj466919JO6KTeyOd3Znne2E2cue4+OIjdXRjQ6mUVyKodcQWcWJHQqTRKlbGJJJ7GjowPnn38+Hn30Udxzzz2YmZlBS0sLHn30Ufz85z9fqTkSdULqgPygdhX8oM0NQjR4XbP9A5P4we6X0T9wGiOnsugfOD332ZuOIo/noquyZwtbpKdyo69S+Zr1/ViSvK+EVfK+qz3iOGZnO1t5Ay8HXCR41JASYjI0nsZUqYzImu8fOzTOtnG0OH7uvXi6O28oXNPW1oYvfvGLKBaLeOihh8r/7ZxzzuE+OYINcmSAjkR4WfZaIVENftDmBiEavK7ZUrp85aKllC7vRXg8F6+5ZLOjg3TNxZvrHhPg9360LDi21nBKF62V87a02uqrEhb887wtjCm85CUKV+9J8MNdJKv+DYO9R0cds85E2fRe0kkcHx/HnXfeiauuuqqscEqIAzkywI7tXY4pRTu2dzGNS6Ia/KDNDUI0eF2zvNLlecHjudi1IYpIi6/ckFqRJURafOjaEH3jP14CXu9HSQIUZa55trToc50MT2TQunZOidVnK7G2rg0yXwdujiuLQysadAyIEj5VhmlZ0A0TRcOEbpgwLYupp6Hom95LJsn7fL4F/175mfA+1HfPPgY3XbuVyzEQSVRDJHj1tiQIXtA1O0+jn4t7j44i6FNQ9NuLNlWREfQpzGI4vN6PPtWWuJcVaZGdbaEZDKhVPY+9utBUFAmG4dAnUWmiECUhHLFwwO5puIi1EX/dY4re73dZldSSV6W0CFd4KNiJBh0DfvBQdKTNDUI0eF2zHYkwBhyaxrOmy4vE0HjaUaG6seuRxoWNOtujsCwgkyuWndpIyMdUP8hroclLNdWvysg5KOCzNCUnCP7YaeElEV4LgGSBKaws+gbikk7iK6+8gquvvrr8eXx8HFdffTUsy4IkSXjuuee4T5AgmgmRZPRLio4lSoqOABriKHr1exOEEzyu2R3bu/D93S9XORys6fIi4VYnpDHUCQH8nl+92zZicKzasWdZFPZu2+h4HbAuNIN+xbFdR9BFobVWdIco4lJ24sxEgvP2i1fjTeNTORiL2rQYpoUJhoh95QbiVFZDe9zb67rFLOkk/upXv1qpeRCEUA4SD3g6XTzYe3QU+YKOdMXCJRryebInGkGICM90eVFwb3bO5sjw7Om4eA3ciDUxjzHXhP3QivkFC2NFlrAmHGAa13Tph+hmJ5oMj14Gmdmioz09qzGNK3Jp0pJO4qZNm1ZqHkSTI5qDxAORGlEDK5UGRhDNTbNH1XmkbwL8BCX2Hh11rB9keY7zGBNYeGwNw4KiSA05tj5VhuHQQsLN4SfOTERTjqUIeDX1d3cliAYimoPEA9FUsHilgREEQZTo3bYR4ym7p+FiOwu86vx4PMdLDbgXZ22wvhsqj61PlcvPdNZjGwmpyDs4iZEQLTkJ7+KaHrvSE/EQdMd6AJ8ioeiwU+FrIiUw0RwkHoimgsUrDYwgCKIEL1EgXoISPJ7jflXByZmM3W8RdtaGVjQQi7KlhfZ0t+I/f/sa/jCUgmnZ/Rf/tDPOfGyzeX1ZdoLwAmrFRsliOwulUqpURkM84heqZICcRA/g5CAuZV8OotT5ieYg8UA0FSxeaWAEQRCV8Ei55el8/mD3y1VRP5bneDavLWgpYQEwDAvZHFut1Hf6fo+XBlMA5pVOXxpM4Tt9v8euHefWPa5TFHEpO0F4gS0b1+CPI9NVNbpb3rSm7jErS6l8qixcKRU5iWcw/QOTCxTRxlM5DI6lcdO1Wz13cYrmIPFAtNYPvNLACIIgVgJe9Z75ooGCZsC0LBiGxVyLl0prUGQJpmVL9EsSIEsSUmk2J/HgSxOudhYnkRrUEyKyY3snvtv3EtKzRZiWBVmSEG3xYcdlnXWPKXopFTmJZzB9+wcxtUhYZCpdQN/+Qc9dnKI5SLwQSaSCzhlBzCNK1kYJ0eYrCn37B5HL61BkCcpcNVMur7O/d0sFU1LFZ0aKhnNduZudIJaDIktVLSVKdq8S8CnQ/GY5CyDgYyufSU7lkCvoVeJQopRSkZN4BjOczC7LvtqI5CARNnTOCEI8dWbR5ssLHo4yj/duPBrASMXfl9JN4+vYahJ9inMNlk8hFVKCHTehc68KoPNQEfarMk7O5Mv1xJIOaEUD8Yi/ATPmDzmJBNEEUNSAIPghWkqRaPPlAU9H2bSs+UUhAJkxchIOqlAUqWrMcJBtCXfxOW3Y/7sxRzsLqiI5tg1Qm0iMjxCvpQQPAcVsXp+vJ56r+zUMSxgRJ9ou8gBuoXfWkHxHwllApKONhEWaidJiaDyVg2nNL4b6ByZXe2oEcUYgmjqzaPPlwVKOMgvxaACGYdcOwppfFMYZlEg13cS6NUEE51pVBAMq1q0JQtPZFtu7dpyL7W/dUK6Z9Kkytr91A1M9IgAE/M4pegG/9+ISbo4rObTNRyIWcrHXL6CYShegKFI5eipJgKJIC3pMexnv3bFNSNCvOO4qBF0etLWyY3uno8oaSxEuIR4UNSAIvoimzizafHlkQvBylHlE/RKxELJjaQc7+/nateNc7NpxLhKJKJLJ6v9HPQR8CnIFHWZFJqssAwGf9+ISsYgfp6arF+wxQdIBicbBS0BRliTIigRJkmAJpt7kvTu2CYlHA5Bgv0wkCeV/Z9l5BOyUmY9fuxU93euwaX0EPd3r5j6TY9BMUNSAIPjitojwqtKvSPPllQnBI2oA8In6dbRFcHo6j3xBR7FoIl/QcXo679msIJ8qQ5Vl+NX5H/uz93ro5goG5EUrYVm27URz0dPdip1XbkF7PARZktAeD2HnlVuY1swdifCy7F6DIokeIBz0Ldx5lOZ2HkM+5rFJWIQQLWpAEKIhmtKvSPPde3QU+YJelRHDmgnBK2qQiIVgOrQGYnneHjsxCRMWSkKRlgVAsnDsxCTed1lX/ZPlRGd7FAXNqGolcBZjD92SwKuTnYnFg4oV7CEaSKPXzDu2d5Vb0RmGBVW1+0nv2N7VsP8HT8hJ9ACabiAS8iE9W4RlWZAkWyJXK5IMNcEO9aAkCP6ItiEnynyHxtML6nd03UQqXYDEKJHIy1Hm8bwdHEvDMhc6Q5Zp21kppfKmMhriEX9DjkFHWwRHXjm1oA3IbF5njnz6fLLjusjHkMZq959caDMtb7dpIMShp7sVN127FXuPjmIqqyEWbsw9tlKQk+gB/KqC2bm+Sqokw7IszOZ1tK+jbGAvw+PlygORogYEQRCVOLVoAOzNVVZ4OMo8nre8VCL7ByYXRDlGFAmDY2ncxFiWMjyRQTwaqIr+Dk9kmOaruGwMsDh0mXxxWXaidqIhH9K56uMYbWHPkhMRwcoRAZCT6BEs6KZZVeQt5BXVJFTKp/tU2fN9xkSJGhAEsTKI0hanpLxZbfdefVuJRj9vfaqMglbtFLsdm1rp2z+I0w493Pr2DzLNPzmVc+w3x1oHXzScNwx0l42EWjBd/tTNTtROfE3A0Ulk1dsQCdHWioshJ9EDjE/lqh5IpgmMk7CIZyHFUIIgRIVnj8BG09keRV4zkKmob4u0+NDJWN8mEp3tUbz6+nSVYmrnhijTuIPjmQXRSAuAaVgYGmeL+CViIQyNpasiiazzdasVpP10b+IWOWaNKPPk2QOD2HN4BJlcEZGQD1ddsImp7lf0teKq5zOm02nceuutuOmmm3DDDTfg8OHDAIDdu3fj3e9+Nz7xiU/gE5/4BF544QWYpol77rkHN9xwAz7xiU9gaGgIAHDkyBF89KMfxY033ohvf/vbq/l16iIz65LuMKut8EyIWiHFUIIgRIVXj0AedLRFkJsrx/ApMhRZQq6UKIf6AAAgAElEQVQB9W0isWN7J1oXKaa2rgkyt7NyT+VlC6N1tEWQShfsCJ81X0fKfM7cskoZygepTyI/Ftd6vpF9tXn2wCCe3Tdor8kte23+7L5BPHtgsO4xRV8rrnok8d/+7d9w6aWX4uabb8aJEyfwhS98Ab/4xS9w7Ngx3HHHHbjuuuvKv7t7925omoaf/OQnOHLkCB5++GE89thjuPfee/Gtb30Lmzdvxi233IJjx47hvPPOW8VvtTwMlzvGzU6sPqQYSvBGlHRAQjxEWrjwqm8DxLnHSu2sRKkrH57IIBRUq6K/rOfMNTWUYanEwe8kOMNL5XbP4RFXe73RRNHXiqvuJN58883w++2mpYZhIBCwc5WPHTuGl156CU8++SS2bduG22+/HYcOHcIVV1wBADj//PPR39+PTCYDTdNw1llnAQB6e3tx4MABoZxEWZJgOORLyIzqbQQ/SDGU4IlI6YCEeIi0cOFV39Y/MIkf7H657HyOp3IYGkt7tpcwj7pyRQKc/C7WINrQeLoc/S2pm+byOnMaq+WSb8rSoJw26cUj2uLDjEMGHqsgTsahfhIAsi72WhB9rbiiTuJPf/pTPPnkkwtsDz74ILZt24ZkMok77rgDd999NwDg8ssvx7vf/W50dHTg3nvvxY9//GNkMhlEIvPpCoqiVNnC4TBOnjz5hnOJx1ugeqTwvaMtgtfGq6WsO9oiSCQYc/g58OLxCfzXC69hbDKLDa1hvPuSs3Dh2W2rPa0V5V2JKNaubcFzL7yGsdNZdG5Yg6sbcBzo2K4MXryvKjn4n8cdRSn+v+P/P3t3HiZVdeYP/HuXqurqquoFaBqQpcEEoiAKIhFBVNwBlwyjo2N0JpJonKjRjIqaRY248ERj4hodNWMyJsElGRU0msQFEQfjgvxAhWi6gUZomqaXqura7/39UV1Fd9e92N2nTte96e/neXySPjSHW8utuu8973nfvThhdt3gH5ADOP01c5NFxx6MX7/4keV4MZ/nYsw1trYCu/YWBhdjRoh9P77y1Idoi2S3dChQkMmYaIsk8cq7jUPmHPPoGlKZdOG4RxN6bjMGLFuUGIYp9p6wi9vMgb/XFEWx3NSoKIq0zxzOKzZnmU+3DBLLfLrQvBUBH8LRwm1eFQHvgOeVda04WAY1SDznnHNwzjnnFIxv2bIF3/ve93Dddddh9uzZAIAlS5agoqICAHDiiSfi5ZdfRigUQjQazf89wzAQDAZ7jEWj0fzfO5DW1k7Rh1M0S46bhIef24zOeDq/Kb28TMeS4yahuVm8D1Ix9V7h2L67A48/vwntx01y5N1XmcYN8+PfT5uCmppQ/nUSeb3c+Ny6JV2ru+6vl1M1NnVYplDtaAo7/thlcMNr5ibjhvlx5ty6gvTFccP8RXuei/WaHTVlBJ7d3VEwPmvKCKH56z9vt1yBqt/ZLnzcbvlctKsWmkobQs+BpgIZwygotKOpitC8B4gRBzyvrqvI2FSOlfWZw3nF5mxpt84iaGmPC807//DRWPVWQ8H4sYePFpq32NeKMtgFwSUvXPPpp5/iu9/9Lu6++24cd9xxALKpA2eeeSZ2794NAPn00ZkzZ2LNmjUAssVqJk+ejGAwCI/Hg+3bt8M0TaxduxazZs0q2eMZKF1XoaoKFCX7YaoLlraWxU0FD9zGbc9tLqhtao3BMPenRG6qbyn1obleTZXfZtx56YDkTtMmDse3z5qGH/7bLHz7rGmODGKA7HEuOW4Saqv9UBUFtdV+LHH4jTO3fC6m7VpK2Iz3VVXAusVBZdArNK8MdbXBgj6LmqoMqeq5gLsK+MhKEV48pw5HHZJd4cvdQDnqkJFC1U3druR7Eu+++24kk0ncdtttAIBgMIiHHnoIy5cvx+WXX46ysjIcfPDBOPfcc6FpGt566y2cd955ME0Tt99+OwDglltuwTXXXINMJoN58+bh8MMPL+VD6rfV6xoQ7Uzl72qapoloZ0q4V5EMbip44DZue27dXtrZydy+j4GomGTsxxtbE0D9LottHjUBoXnd9Llot5VPvKVEtliN2jvAcGCviqmThuOznR1Qu7JOFSW78jl1krNeqxxVsS7UowrGcjICL1nHKsum+hY0NkcxesT+z4DG5ig21bc47twdLCUPEh966CHL8Xnz5mHevHkF4z/+8Y8Lxo444gg89dRTRT+2wdKwO4x0tzPJBGCYJhp2O2s5GnBXwQO3cdtz67ag1k1yX0huqWZI8rglddFtFh1Th/95ZSsi3aqmBv0eLDqmTmje5rYY4ol0QTXWofS5mEwbqAr5Cp7bZNp5QWLjngiGVZYVHKtTe/lpqgIjU/g89l4N7S8ZNwzk3YSQY+3GXYgl0gXvBSfe4BksJQ8SCUhZnPAHGi8lrnDI47bn1m1BrdvIWD0hd2GVW3mmTRyOr0toK+HVNezoiOT346XTBpKpDKpC1imYpSRrpaemyo+m+n2IddVZSKWyqXt1o5xXfKq5LQa/T4e/yNVzZfF6rIsNeT3OKMTY3YH2kDrRtqYwWtrj+dXTZMpAIpmxLMI0VDBIdADDZjnfbryUuMIhj9ueW7cFtURu46bURTeScSMmGk8ik+mZGZTJmIjGCqsmltqYEQE0Nkctx0VEYil0xvcHMiaAznjatsVAKbntZmc8WRggHmic+q4jmixIr80YJjqiiRIdUekxSKR+4wqHPG56bt0W1BK5DVO63ac1nMymBJpmfo+bqihoDTsvSJx9aC0+f/PvPZrUq2p2XMTWHW39Gi+ledNHW6YdO/Vmp11NIcFaQwQgkbJ+Eu3GhwIGiUQ0YG4Kaoncxm2rHJSlqgpUOD9FrXFPBCMq/YjEUshkTGiaUpT9eGmbrTJ246XW+5Vy/ivnDm4rXOO6TZSDgEEiERENKW4pBsOUbvcZWxNE/a7Cvo5jRzqvpYKslWoF1vvORGMDGfOu3bgLZT4dZb32JA61lG4ZAZ3djikH7qQCAAT8HkQ6C1OiA35PCY7GGZzZjG+IsdsTO4T3yhIRSeGmPnZu6xFIwKJjJqA65Mv2OlayPZCrQz4smjOh1IdWwKur2NceRzyRRjKdQTyRxr72OLy62MVHqNz6otpuvK9kFEJpboshlkijuS2GXS3Rbj8PrZRuu+IsQ6loy8lHjYPW1a8cyF6Da6qCk48aV9oDKyGuJDpA0O9B2OLuRXAI370gIpLBbcVgmNLtLtMmDscFEqqmrnq7Aa9/sBORWApBvwfHzzhIuMl3NJ7eX6ijq09gxjQRjYsVQRk9PIBwZ1uP4E0BevSfcwqvrmJneH9hknTaQFs4geqgt4RHNfjcVolUhsVz6vDJtlZ8sq0VJrLv2cnjq4TPMzdjkOgAlQGvZZBYGRhaH1JERLKxGAzJVuzAftXbDVj1VkP+50hnKv+zyAVsazgBTVPy7ToUJbufsjUsVs2xLdprXmTnbYs4r3iPbbLqEFpBAyBlP56iWP91pz61q95uwKeN7dC1/UmWnza2Y9XbDUM2UGSQ6AApm7JUTt3kTUTkViwG4z5u2UOaU+zjff2DnbbjTrx4TaUNqIoCVVN6jWdKdET2kukMqkM+hLtVNw35PUgOsYqWik1EJ5JuepBNi5WDHLiiDLjvPBsM3JPoAHZ37faFeWebiKiY7Iq+sBiMM7lpDykg53jt+gtGBfsOVod8yGTMfGxgmtmejtUhn9C8Ht360tKrizV8V22uWO3G+6Kmym8zLnbTyG21JkybFUO78b6YfWhtwWtTjBYrskRiKRimiXTGQCpjIJ0xYJim8HnmZgwSHcDujtVQu5NFRCQbi8G4y4H2kDqRjOO1q08gWnUxUKZD03oV6tAUBMrEkswm1IYsi/eMrxWr8OrzWAeZduN9MXZkEHvb4+iMp5FMGeiMp7G3PS5cjTZYZv3aOLXWhIxKpLkWK+VlOrweFeVlOkZU+oVbrMji07X9N03M/TdNvALvL7djuikREQ0pLAbjHm7bQyrjeI+fcRCeX1tfsMfv+BkHDXhOAEimjXzhPNM0oSjZPonJtNhWl3nTR6OpNVbQVkJ0tV7GDfV3Ptq9v3hPl4xh4p2PdgulGJ48e5zlazaUKmU2t8WQSGWQSGZgmCYyGRMeXXXsuVsZ9CJssWo4lOuDcCWRiIiIHElWOqAsMo63blQIQb8nvz8sF8zVjQoNeE4gm/7ZGU9DUxV4dQ2aqqAznobXI3ZpKGu1XkZK5K6WGBSg4L9dLdbBfl8tnlOHrx5amy+ComsqvnporWP3ttm95iLvhVQ6g45IEoZhAiZgGCY6Ikmk0mLVc2VJZYyCvpCqAqSGcH0QriQ6gIwmpkRERG43b/poPPvG3y3HnUjG8a7duAuVQR8qg76CcbHAq/gVLXPcslovI/AEsntTG5ujPdp+NDZHsam+xZHPi64qsKo9qwtciLZHUpbvsPaoM/f4dcbSBdfihgl0xp15vIOBQaIDyKgqRURE5Ha5C+pi9x2URcbxykq5TaYN+Mt0RDpTMMxsRdJguXi6KSCnIq2qKjAsVnVUgUAmUOaxLAwkut9z7cZdaIskup5bM//cOrUfayxhXXnWbrwvIjbBlVMLwcRT1o81nnReVd7BwiDRAVRVKciJz40TERENZW5Zlcop9vHKatvi1VVEu/YjAtnVs2hnCqOqrVNm+ypX4TUnV+EVgNDzkr1xXtwb6ifPHofn3qzvcQ2mFWHv4NbGNrR36wuZMU20R5LY2tguNK8sdrcFRG4X2C3GihTDkSlj047ObnwoYJDoAGUeDal04ZuwzDt0KyoRERG5UbFX0eZNH43/eWUrIt16+QX9HuGU22g8vT846kpoypgmonGxPWMHqvAq8jzY3TcXuZ9eNyqEYLmnYMVPdL9nR9QqeRPoiFq3PCs1tzW+p8HBwjUOUO7XLTfLltuUUCYiIiLnkdXXsfe1ejGu3VvDCcsWGHa9m/tKVnqsXZ9FkRYFazfugs+jwefV4NFV+LwafB5NuMWKYbP4ZDdeagGb60278b5wW69Iu/fRUG6BwSDRATyaarlZ1qM59EwiIiKiAjL6JK7duAtlPh01VX6MHh5ATZUfZT69KL0iVUWBrqnw6hp0TYVahCt4WRVpdd36kjVXQXQgtjWF0RZOIJ02ABNIpw20hRPY1uTMXn6yHDQiYLlYcVBNwPov9IWMHFaJJtSGoPV6EjRVwQTBVWU3Y7qpA+yx2GsAAHts7sYRERGR88hYRZO1Mje2Joj6XR2F44KN5GVVpFUUQNeUgt6DInGt1Vaf7PhQK1ZiFhRRtCuq+I9q6qRh+OzzdqgK8u8vRQGmThwmNG8u/bw1kkR10Ovowlu9cSXRAZI2H1IiDWKJiIhocMlYRZO1MrfomAkoL9ORMUwk0xlkDBPlZToWzZkgNK+sPokeXc2vfHo0Nb/y6bFJQ+3rnIZpIp0xkMoYSGcMGKZpm9r6j2pPW7yggGLGMLFH4EaEyxYS0bgngmEVZSjz6fDoKsp8OoZVlKFxz8BXlbunn5umWbT088HClUQiGjAZZc6JiNxKxiqazF6RPo+GpNdAxjChqQp8Rd9/VbyQYEJtCKaJggI+E2oHvvJZFfChpb0wEKoMekUO1XXs2lI4tV2FDM1tMfh9Ovw+vdf4wANlWUWcBguDRAfw+zTLXjR+39C6k0XuIqvMuSxuTvkgIneYNnE4GnaH8foHOxGNpRDwe3D8jIOEPmtkzAlkL1QTqQwSyUy+sqdXV4UvYGV9N8ybPhoNu8OW4wNnE8QOoTRLAEjZtHmwG/9HJKPVjKxU8cHCdFMHOP3oCZabZU8/Wizlg0gmGQUaZHF7ygcRucOm+ha8t6UZoXIvRg0PIFTuxXtbmoU+a2TMCQB/a2xHeyQJoyvN0DCyvfz+JtjLT+Z3Q7IrqE2lDSSSGSRtGqD3VVs0uT9O7Pa/bdGhs4IG2FfLHUrlE+1uNojchJCVKj5YGCQ6wOI5dTjr2IkYVuFDmVfDsAofzjp2IhbPqSv1oRHZctMdMjcFtETkXrKqmxZ7TkBeimFzWwzxRBrNbTHsaol2+1nsu2H1ugZ0xtPQVAUeTYWmKuiMp7F6XcOA50ylDahq1z5HvWufo6oMucI1ik31H7vxUpLRLxOQs5d23vTR+XNhR1Mkfy4UI1V8MDDd1CEWz6nD4jl1qKkJobm5MJ2CyGlkpGbI4qaAlojcy03VTQ2blEpTMNXSq2vYGY7mf06nDbSGE6gK+YTmbWyOwjDNguqmjc3RL/qrtnKFa3rPOdQK15T7dIQtbg6UlzkvTBgzImD5mo8ZIdCuo8u0icOLvg2l99nkpkRmriQS0YDISM2Qxe0pH0RUfJvqW/CL5zbh1if+il88t6ko6eduqm5aEfBC69ZCQlGyW11CAdGiLXL2+WUME+mMCcPMTmWYQDpjFlTl7I+qgHXgOtQK11QGPdbjAevxUpp9aK1lT8fZh9aW5oAOYO3GXfB39TgdVxtETZUf/iL1OB0MDBKJaEBklTmXwU0BLRHJ132fsmGiaPuUZXzWyPr8On7GQflUS6+u5VMtj59xkNC8ybSBqpAPuq4CCqDrKqpCPiTTYkGiXeajWEakadlWY+gVrjEtAy+RLZ9yXi9g89/3FaTBKoqCzfX7xCaWoHvqdfd0U7dkMTlvHXmIYuVFciMZqRky5I5x7cZdaIsmUVvNdh1EQ5ms0vTdP2ua2+KoqSoT/qzpXt00EkshWKTqprm6B69/sBOd8XS+aqpoPYSaKj+M1lhBKwHRlc+0TU9pu/G+yAW0vdtqCAe0sF5Pdd4Ov6zOWBq9F2QNE+iMC+xPldQocVtTGIZh9nguDcPENovKt6XWPfVaUZSipV4PFgaJDtC9XLRHVx3fSoDIjXIBLff9EpHMfcrFvnnWvbppqDybBvnelmbUjQoVJVAsdj0EWX0d7dJKRdJNa6r8iFoEF6IB7fBKH/a2JyzHnShus2QYTw58KVFSjIhU2rCcIyVws0Aed7dYYbqpA7DyIhER0eBx0z5lmdcIuX2Z3/vZG0Xblzlt4nAcOaUG4c4kdrVEEe5M4sgpNcIBrYygY+zIINrCiexqpJldlWwLJzB2ZFBgVuCi074Cn6fnJbbPo+Ki074iNK8shk2gbTdOfdMj9RrFS70eLFxJdABWXiQiIrKW247R3BZDTVVxUsVlrXbJIOsaQVYWk7SVTwnX1Y17IqgO+RDulm4a8nvQuCciPLeuqUimjHzVVF0TX5fx6ApSFgGGRxeb26OryFisGorMa5tyK5hzK2uvI1D8z5ruqdceXc2vdjrxZpSVkgeJpmli/vz5qKurAwAcccQR+M///E+8+uqreOCBB6DrOpYsWYJzzz0X8Xgc1157LVpaWhAIBLBixQoMGzbM8nfdpKbKj4bdYURiKWQyJjRNQdDvQd2oUKkPjYiIqGS6BzIAihbIyNg7KIusdkNrN+5CeySBcGcKhpkt4BIq9wjvy5S139N2JVEgeGxui6HMp6Os1/5J0QD8qVc/RTSezv9sAojG03jq1U8xbenAnwPFJvQSjY9GVJZZtpUYUTnw95jHkw2SC8YFA1p7Ys/CpvoW/M8rW/P7U5taY2jYHcbXT5k84Petm25GWSl5kLh9+3ZMnToVv/jFL/JjqVQKd9xxB5555hn4/X6cf/75OOGEE7Bq1SpMnjwZV1xxBVavXo0HH3wQy5Yts/zdmpqaEj6q/hk7Moh3P9mzf9NwCq5qtklERCSDrICjJ2enfsm60Nza2Ib2SDL7g5JNLWyPJPG3xnahed2UHSUrAN+517p3o914X6Uz1u9Vu/G+CpTpUBX0KF6jKtnxgbIL3kW34/m91j0d/T6x3par1zVgX0c83zMznTaQTGWwel3DgD9r3F40r+RB4ubNm9HU1IQLL7wQZWVluOGGG5BMJjF+/HhUVlYCAI488ki8++67eO+99/DNb34TADB//nw8+OCD+Oyzzyx/9/TTTy/ZY+qvNRt2WlaVWrNhp3CVMSIiIrcajFRLoHgrlDLIWvXsjKUtx6MWF+D9ISvwkkFWAC4rQDJsJrAb76umtpjldegegfNM1j7HyqDXMkisFOzv2dAUQaZbsG0CyGRMNDSJpR67uWjeoAaJTz/9NJ544okeYz/60Y9wySWX4PTTT8e7776La6+9FjfccANCof2ploFAAJFIBJFIJD8eCAQQDod7jHX/3S9SXV0OXRe761AsLR2FFbBy4zU1TDl1A75O7sLXy334mrlPMV6zsbUV2LW38Dt9zIig0Px//eMWy7S3d7fsxQmz6wY8rywn1ISKflwm0DNDT9k/LvLcLjr2YPz6xY8sx2WcxwoGfrwn1IRQWVmOv7yzHbv3RTFqWAAnzh6PmVNGFvcgu5H1WSYyb35FuZe2yMCvQz0eFUYi02OdXgHg9ahCx2oC0FSlR1VbTVVgQhGaN5MxLDNWMxlDaN73t+zBn9/Zjt0tUYwaHsBJkt9fxTSoQeI555yDc845p8dYLBaDpmWDtVmzZqGpqQnBYBDR6P4l+Wg0ilAo1GM8Go2ioqLC9ne/SGtrZzEeUlEc6I6T2+46DEVuvDs0lPH1ch++Zu5TrNfsqCkj8OzujoLxWVNGCM3f2NRRsHICADuawkPmvRYq96Ajmsyn1ykAVDW7L1HkORg3zI8z59YVrHyOG+aX8tyaELtWam/vRDyRQiqVQTyRQnt7p/Bx9k7d7D4u6/0lMq+M69ARFT40Nve81jYBDK/wCR1rLJGGpirQVKXXeEpoXk1TkckUFu/RNXXA8/YuDrV9dwcef34T2o+b5KiMBbsguOTppvfffz+qqqrwrW99C5988gnGjBmDgw8+GNu2bUNbWxvKy8vx7rvvYunSpfj888/xxhtvYPr06VizZg2OPPJI2991kwN9mBAREQ1VslIt3ZQSKcvxMw7CqrcaoGoKFEWB2RUpHD/jIOG5i90rUhZZaceapsKw6NunFaHCqVsEyrzQ1RgM04RpZquPqoqCgF8sLdSjq8gYZsFKokcwO7CuNojPPu8ouGkyoXbg7VAGZ0+1PCUPEi+55BJce+21eOONN6BpGu644w54PB5cf/31WLp0KUzTxJIlS1BbW4vzzz8fy5Ytw/nnnw+Px4O7777b9nfdRNetK0Dp0ipAERERuYOMgMPtVQeLIVfz4PUPdqIznkbA78HxMw5ybC0E25YKAnPKuoi3u8k/lG7+J9MZDK8sK2gvYnW92x8eTe0RIAJAxjDh0cSe3EXH1PWobqprKoJ+DxYdUzfgOd1UxMlKyYPEyspKPPLIIwXjCxYswIIFC3qM+f1+3HvvvX36Xbfp/eGnQLykMRERERVyUwsMmRbPqcPiOXXuSOmWECXKuojvHcR80Xiplfs0dCYKUy3LBSqG1lT5sXVHGxLJDAzTRCZjwqurmCDY3q2lw/q1sRvvq2kTh2Pe9NF4/YOdiMYMlHm1ovRJdHPGQsmDRMouk/feMmwiu8xNRERExeeWlEg3KnZTcllygUzvXpGTx1UJzSurVYXfqyFm0fRetP2D3WGJHK5HV9HWrSBOxjTRFkkK90mMWQSzBxrvq031LXhvSzNC5V6EyrMpse9taUbdqBD7JBIRERHR0JEL5lojSVQHvUUJ5qS1F7ELWAQDme6VPQ0z2ytSXsN3MTXVfmy3aMlQU+UXmjedNiwXZNMW+yr7auNnLf0aLzUZqcfsk0jCMoYJRelZXUpRxHvJEBEREVnZVN+CJ1/ZinAshUzGxE5NwbbdYVxwymShi1hZ+/wUVYFpcV2kCGRdfbytFZqmFBQr+Xhb64DnlKmx2brFm914X+m6ioTFCqVIsGzXb1O0D6csslKP3dwn0Zm3SoYYn64BZtc+RKUrvd4EvB5n9HEkIiKifyyr121DaziRXy1Kpw20hhNY/fY2oXllXWz3bnnwReN9EYmloCoKdE2FR1OhaypURXFsIGPYLOzZjfdVTaX1HrkRNuN9IWHhV6qaKj9iiTSa22LY1RJFc1sMsUTaNfsHZWCQ6ACVQQ9MZE8c00T+/1cGPKU9MCIiIvqHZLsqtUdsVcou9VH0YrvM5sZ5mXfgN9SDfuvrrIDN+D+u4od0dqG7U6ttjB0ZRFvupomZvWnSFk5g7MiBt8BwOwaJDpDKmAUnjQIgJbYHl4iIiGhQzZs+GvFeKzLxRFq4WIdtGCOwNGXXE7IYvSLdxG6VV2T11+51EXm9ZGrcE0F1yJdtP6dkU3CrQz7hmyZuxj2JDtAZTwPourvSrcRzZ9yZ6Q5ERETkbmNrAvh0Z0dBU/KJNQHhuROpTEHrA1HxZLpf433RvVdkNJZyfK9IWVI2BWrsxvtERmNLiZrbYgWHa8I9PQ1lYJDoAEkZJycRERENOre0fxhR5ceWHe09xjKGiRGClTJXr9uGSCwFs2vJyDRNRGIprH57m9DzkLHpx2A33le5XpFDWu/qid3HB8htK4leXcXOcCL/cy7dtDroLeFRlRaDRAfQVQUpBTBymxEBqIrYZmwiIiIaXNLaP0iw8VM5LQq2NYV7BG4msoHctt1ilR0lxDHUxauriFtUNy3GCrB72LyRhvAbjEGiA/h9GqLxnukShineHJWIiIgGj6z2DzJE46n9l8XdUgNFK3tKSV1Edo9YMlU4hy4YyLhl5VemEZVlaGyOWo47jaws1mQ6g+qQD+FYCumMAV1TEfJ7LN9zQwWDRAdIJK3fgIkh/MYkIiJyG1ntH2RQFCWfEtp7XISuKUhY9DPUNbF57XpHi/SUdtPKL5DtW2gVbIv0MwTk7PeUtfIra96aKj+aWmMo8+m9xp0XKA+WobSO7Fgxm5MwlmB5UyIiIreQ1f5BhtHDrY/Vbryv7B6r6HMgY0/igVZ+nWjS6Ar03omkKsCkMRVC87aGk/0a74uQTRsRu/G+sls5Fl1Rtqu+K1qV180YJDqaQ3f3EhERDZJN9S34xXObcOsTf8UvntuETfVie0cGY5wAACAASURBVOZkctOF5rkLvoyKoBdqV9Shqgoqgl6cu+DLgjO7p0NermF67wbqTlz5BYCpk4YVrPQqioKpE4cJzWu1onyg8b7oTFgvgNiN95Vqs2RoN95X0yYOx5FTahDuTGJ3SxThziSOnFLjyBXlwcJ0UwfInvDFT/kgIiJyM7elA+aOKbvHLY6aqjLH7nGbNnE4li46BGs37kJbNImqgLcox9oaTkBTlYLWGq3dKkcOhKYqSFuklooU+ZNV0VJWSuTmv++zHq/fJ1ShVcZ+z7TNCq/deF/Z9ssUmjX7WfPelmaEyr0IlWdf//e2NKNuVMiR5+9gYJDoAKrNB5zdOPUPN6UTEbmTmwrB5EybOLzoxybreyx3rDU1ITQ3i1UfzUkbJgzD7LFuaBimZYDXHz6fhnSscBXK5xO5lJVT0VJVFGQsokTR1a5tTeEewTeQbVsiWjnWTWSsegLu/KyRjUGiA3h1FYkhX3pYDrfdhSYiov3cVAhGFrd9j3l1FUkJ1zT2aYYDnzOZzkBVlR7tH8q8mnBFyzKvhs54usfqltI1LiKRsq5VYTfeV3aP14mVPWVVz+VnTSFGIQ6g2VT80jW+PKLctimdiIj2c1MhGFnc9j1WXqZDU5X8YpzS1fc5UCZWsCSZNqAABf+JBAfhzlRBf8B4MoNw58ALtgBAdchXkP5odo2LcFuDehlkPQc1VX7L/alD6bOmN0YhDqAqSkFOffcPWBo43hkiInIvNxWCkcVt32MTakMIlnuydRWUbH2FYLkH42uDQvPqqgJVVWAC+f9UtfD6qT/abPZJ2o33nZydc3bXhbxeFDd2ZBBt4QTSaQMw9+9PHTtS7H3rZkw3dQDTxP78/a4aNoZhDqk7Q7Lk+t4Ujg/dO0PkDtxLSyS3EIxbzjGZ32O556A1kkR1sDiFa8aODGLD3/ZCUxVoXXv+OuNp4Yvt6pCvoOF7xjCFVues9g0eaLyvmtutg0y78b4KlnkQjqUKxwXbSsigqoBhscirCi5PaSqQsZhXNPmucU8E1SEfwrEU0hkDuqYi5PegcU9EbGIXY5DoAIqSvRuWMcz8TSauJBbHvOmje+zl6D5O5FRu24NEJJOsQjBuOcdkfY91fw48ulq056BxTwT+Mh2RzhQM04TatZIofrFd/NU5j2bTnF4w4pC1b25cbRAfNbQWjjtwtasi4EWbRZ/FyoBYyq3Xo1n2Efd6xPZ7NrfFUObTUdarEJJTV+wHA4NEBzBM07JaFVcSxbmpHDlRDqusuY9bVqUoy03nmKzvMVnPwbamMGLxdI+VxFg8jW1NYkGi3cW6yEX8UYeMxLr/t9ty3Ik+3dner/G+UlUFhkX1WZEq+5PHVmHrjjaEu90sCJV78OWxlSKHioRNMR278b5i5lkhBokOkEnb9ZJxXlUpN5JxF5pIJrftQRrq3LQqRVluO8dkfI/Jeg7sV9HEKnDK6Lu3dNGhAIC/frwHqYwBj6biqENG5scHyqMpSFgEXR6bQoV9JasKqd1RiRztvOmj0dQaQ2XQVzAuwiqYPdB4XzHzrBCDRAeIJwv7/gBAPGE9TkT/2HhH013ctCpFWTVVfjTsDiPSbf9R0O9B3ahQqQ9t0Mj6nPHYtLrw6mLpgPltORbjIpYuOlQ4KOytpspfsH8yN+5EMgIvt2Vyue14BwODRAewOwcFb4oQkUvxjqa7uG1VivYXV8nJVzIcQueYrM+ZCbUhJJKZgjRD0eqmZR7NcpVStPcgU8Vl1WKVM5NMzDzriUGiA8i6O0ZE7sQ7mu7ClV/3YSXDnp8zbdEkaquLEyCNHRnE+1uaYZrZYnwmTEQ6U8LVTcv9OmLJdLb6O7KpkKpg/0VZqeLN7Tb7J23G/xExDd/9GCQ6gK4pSFlkluqCuetE5F68o+keXPl1H1Yy7KmYhfI2/70l384rv6lNyY4vnlM34Hkn1IYAEwWBvcgK5dqNuxBLpAvSjkVTxVMp6/2XduOlptksVoj0oJSVhu/1qJZ7ML0etn4vNgaJDmD34czqpkREzseVX7lkpAO6bfVXxnMgrQVGcxSqokDtdaPbao9ef+QKofQO7EVuxmxrCqMtvL93YS7teJtoDzJFsb6Ic2hvs1DAY9muoiLgHfCcstLwq0M+NLfGemzJUhWgOuTMc9fNGCQ6gPxccCIiebinhyu/sshKWXPT6q+s52Dtxl2IJ9IIx1LIZExomoJQEVbRZJFxMyaVNmCYZkEKq2glVq+uIp606OVnU9Sn1IJl1kFioGzgYYKsGzETakMwTRSs/k4Q3PNKhRgkOoBXV5HMfZjkUjTg3A8TIqIc7jshmWSlrLlp9VdmP8PWrlU0RVGQThtoDSegCK52ja0Jon5XR+F4ERq+F/tmjGkCmW4tNExkfxbN5BpRWWa5cjqiUixAGlHpw972hOW4iPZoYYB4oPG+mDd9NP7nla0FwZzojZjcirK/iCvKZI1BogOUl+mIxlMwDOQDRFWF0GZsIqLBwPYPJJPMyrFuWf0d7H6GScFVtEXHTMCTr2wt2Du4aM4EoXllUBRA05SClUTRrNBAmV6wz09TFaGVOQC46LSv4L5nNiLVLbD1aAouOu0rQvPGbFquxRJi74VoPIVYPA0TQCplFCXbdtrE4WjYHcbrH+xENJZCwO/B8TMOcsW57DZcqnKAqoAvm7+vZD+wVAVQFQWVwYHnghMRDQa2fyCZ7PrKOXXvoAyyngO7foYewX6G0yYOxwWnTMa0icNw0Iggpk0c1vWz8y7iPboKVVGgayo8mgpdy/4s+hy0RZPZgFNBj/9tj6aE5m3YHYaZm6/retHsGhdh2CydGqb1jYS+eOrVT9EZywafudiwM5bGU69+OuA5gWz2yntbmhEq92LU8ABC5V68t6UZm+pbhOalQlxJdARWriEid3JbARByFzftHZRFZj/D3N6uTMaErhdvb5dbVmll7W+TtUr7+gc780WBFEXJthnpGhepHGsXCwrEiNjV0tmv8b6SVZEW4P763koeJD7yyCN48803AQAdHR3Yu3cv3nrrLfzyl7/EM888g2HDhgEAbrnlFowZMwbXXnstWlpaEAgEsGLFCgwbNgyvvvoqHnjgAei6jiVLluDcc88t5UPqt7ZoEoZh5is1mQBgmMJ3nIiIZONFPMnkpr2Dssh6Drrv7fLoaj6wGUrnrqz9bYZpIt0t1dQ0s2MWXSb6JRJLWRbaicbErhdlFFA0bRY67Mb7SlZFWu6vL1TyIPGSSy7BJZdcAgC49NJLcc011wAANm/ejBUrVmDatGn53/3lL3+JyZMn44orrsDq1avx4IMPYtmyZbjjjjvwzDPPwO/34/zzz8cJJ5yAmpqakjyegeiMp2GaXcvxXYVrTDOby01E5GS8iCfZ3LIqJZOM56DH3q54GoEyfcjt7ZL1+ZVJWwdCmYzA0hwAn64hkgsIlf2Fd3oHuf2lqtl9mVbjAxXwexDpLLyODfjF6m2k0kbXwkq2wJDStUVLtCIt99cXKnmQmPPKK6+goqICxx57LIBskPjII4+gubkZxx9/PC699FK89957+OY3vwkAmD9/Ph588EF89tlnGD9+PCorKwEARx55JN59912cfvrpJXss/ZW0TUsQ+zAhIhoMvIgncp/ue7uGVZQhlTbw3pZm1I0KDanzWcbnV8omGLRLQ+2ryqB3f5DYfVygnyEAlHlUdFoUqSkTaFB/8lHj8Pyb9QXB3MlHjRM5VNtVWtEdWtxfX2hQg8Snn34aTzzxRI+x22+/HdOnT8fDDz+Mn/70p/nxRYsW4V//9V8RDAZx+eWX47XXXkMkEkEoFAIABAIBhMPhHmO58Ugk8oXHUl1dDl1wY3KxeHQVhmFmyy7DhKIo0DQFXl1FTU3oiyegkuPr5C58vdyHr5n78DVztr/+cUuP4jW5///ulr04YXZdiY7qwN7fsgd/fmc7drdEMWp4ACfNHo+ZU0aW+rAK2BeCMYXOC3+ZB9UVPnREk8gY2d6WFQEvyv0eoXmtejrmxgc67zfOPAyBgA9/XNeAcGcSoXIvTjumDueeOHnAxwkAyaR1oJ0QOFYAGFtbgV17C+OHMSOCRfssc9tn4qAGieeccw7OOeecgvFPP/0UFRUVmDAhWx7ZNE3827/9Wz74O+644/DRRx8hGAwiGs32nYlGo6ioqOgxlhvvHjTaaW0V2zhbTAcND6B+Vwd0TYGiqPl87TEjAmhuFqtYRfLV1IT4OrkIXy/34WvmPnzNnK+xqSO/R677nsQdTWFHvnab6lt69N3b2RzBlm378HUHVk5N26wkpjOG0HNbHfSiPZKA16Mhk8kGibqmoirgFZrXbq+kYUJo3hOmj8YJvfZ3ir634imbgDaVEZr7qCkj8Ozuwv6es6aMKMr54OTPRLvg1REtMNatW4f58+fnf45EIli8eDGi0ShM08T69esxbdo0zJw5E2+88QYAYM2aNTjyyCNx8MEHY9u2bWhra0MymcS7776LGTNmlOqhDMiiYyagOuSDrquAAui6iuqQz5E9hYiIiMj93NZeZPW6BrSFE0inDcDcX7Bk9bqGUh9aARnVQgFg7Mjg/ucA+5+DsSPFK9K6hl1eqWC+6bSJw7HkuEmorfZDVRTUVvux5LhJjrsBMZgcsSexvr4ec+fOzf8cCoVw9dVX46KLLoLX68WcOXNw3HHHYfbs2Vi2bBnOP/98eDwe3H333fB4PLj++uuxdOlSmKaJJUuWoLa2toSPpv9yPYXWbtyFtmgSVQEvCz8QEZHr5ErIt0aSqA7yu8zJ3FaZuLE52q/xvnJT24PGPRFUh3wIx1LIGCZ0TUXI70Hjni/eZvWPIlDmsdyXKVoQB+D++t4cESTedNNNBWNnn302zj777B5jfr8f9957b8HvLliwAAsWLJB2fIMh98Z08nI0ERGRne4l5D266vgS8m4KDmToXtmzLZpEbbXznwOr9g8iZLU9UFUFmSJXCwWyxVXKfDrKerUtGUrFVU6ePQ7Pr60veB+IFsQB+JnQmyOCRCIiInI3N5WQZ0+0LFk3qGVcbFeHfNjZbdXQRLb9Q/Uw34DnlPWe1TTrIFHTxILEmio/mloLq3CKpggrinW2pmDrQSnvg8Vz6tC0rxN//XgPUhkDuqbiqENGYvGcOuFj7b7ntak1hobdYUfueR0sDBIdgik6RETkZm4qIe+mgNZtZAXggTIdmqYUrCAFygZ+KSvrPZvOWO+Psxvvq3nTR+PJV7Zm0027CteE/B7hFOGuFt2W4wMl632wqb4Fm+v35YPwjGFic/0+bKpvEZo3t+c1p/ue16H6meCIwjVDXe7uxab6fdi+O4xN9fu6fm4p9aERERH1iZsKoTS3xRBLpNHcFsOulmi3n50X0LrNgQJwEcm0gWEVZflUyzKfjmEVZUjaNK7vC1nvWdOmiIrdeH+0RRLojKeRSGXQGU+jLZL44r/0BezSYDWB9FhZ74OnXv0U7ZEkDMMETMAwTLRHknjq1U+F5pW159XNGCQ6QI+KXXB2xS4iIiIrdqsZTiyE4tVVy0qZXl0wv46krc7VVPnh9+moqfJj9PBAt58HHtDJes/apWmKpm/+6o+fIJHqWSI1kTLwqz9+IjRvRcCL3vGgqgChgHfAc8q6EbOrpRMmUPDfrhbntLb7R8Eg0QF494KIiNyuRwl51ekl5CVdxZO01TkZAZ2stgeaan15bTfeV3vbrVcN7cb76pAJ1QW9Eg0zOz5QXl3Fvo444ok0UmkD8UQa+zriwjdiDJvVWLvxvhpbY91GZEi1F+mFexKJiIioKNxSqTuZzuRbCaS7il+E/B4kU4KN7Ehaa43u1Vib2+KoqSorSv0GGW0PvLqKTMboEXipSnbcifa2xaH1qsiqqQr2tg981S8aTyPTbQ9mrtBQNJ4WOVQp+yeBbM/y3H7P7p8JQ7lnOYNEBxhbE0T9ro7C8SF894KIiEiWXJXIMp/ea9x5+ydlWvV2A17/YCei8TQCZTqOn3GQcJVIWcFcT+J7+2SqDvnQGU/3CFxMMzvuRI3NkWwhoK4qp4qSDbpE+i+2hhOWhYZaw2KrnnYLhqLbPbv3LJf3vnUXBokO0P3uRffmqEP57gUREZEsbmskL8Oqtxuw6q0GAICiKIh0pvI/FyNQLPbFtZvalgTKdGiqAsM080GXqohVYpUpnTGQ7raKaJrZ9E0tI7ayrioKVMG2H4NJxvvWzZz5bh1ipk0cjrnTR+fv5pV5Ncwd4ncviIiIZBmc1S5ne/2DnZbN6V//YKdwkCjD2o27EEuk833sdE1F0O8Rblsio5dfMm0gUO5BpDMFEyYURUGg3CNUiVUmu+qmduN9MbYmgM8+7yh4f42tCQx4TsB+DdmZz6y7MUh0gNwHVDyZAUwgnsxg7cZdqBsVGlJfWERERINlqK8adEST+/eMdaUZZjImwtFUaQ/MxramsGUfu20CxYZkrU56dRXRWCrf8sI0TURjKYyqti7qU2oyUjinThqOvzW25/dlmgBgmJg6aeiec27jzB20Q8zqdQ35ClDJdCZfAYotMIiIiEgG1Sa4cmqB11TagGGaSGcMpDIG0pnsz6l0ZsBzyurllyvaYnb1Z8gF4KJFW3Sb1E278b7SVMWyBYZIn8TNf2+B2jVvNt02u5K4+e/sAe4WDBIdoKEpsv/DBPs/TBqaBr5hmIiIiMhOud86mazc7xnkI+mb3LVR78BLZLVLVk/HXNEWRQHQFSRpmnjRlkzvPhVfMN5Xfp9m2QLD79MGPGdjcxSqokDXVHg0FbqmQlUU4fZudsckcqxkjUGiA6TT1huD7caJiIiIREweW4WKoDe/70xVFVQEvZg8trLER2YtF2j1DrxEVj5l9XSURVZlz45O6xRju/FSmji6ol/jNHAMEh1At+mb43FoPx0iIiJyt3nTR6Mq6MPYkUEcfFAlxo4Moiroc2yFV4+uWq5MefSBryDZPVbR56A65LVc9awOeYXmlcWuP6hI39CxNUHL9GDR9m47bLLsdgi06yBrLFzjAHW1QfxtZzsMA/nyTKoKTKhln0QiIiIqvu4VXtuiSdRWF6eypywTakOIdKbQGU/nq2WWl+lC10qyqtwGyrxQlM4eKZyqAgT8zgwSZZg6aRg++7y9cHziMKF5I3Hr1c1IzHmrnm7HINEBpk4ajs8+7wCUbmWCFYUVoIiIiEiaXIXXmpoQmpvDpT6cA/LoKjq7Cr/kMkw742nhrCsZVW7bogkoitIjD1RRFLRFkkX9d4rF79MQSxQWABLak7gngoC/qw2I2dUGxO9Bo+iKn8QeGDLaobgZg0QHaNwTwfCKMoRjKWQME5qqIFSME4mIiIgGFS805fh4Wys0TSnou/fxttZSH1qBzli6oJhMxjDRabMKVmqnHz0Bz71Z3+OYNVXB6UdPGPCc25rCiHSm8nNmTBORzhS2CRZlVFXFslCPSE9HQF47FDdjkOgAPaprmd3HxaprURa/sImIqDcZ3w280JQnEktBVRSovdo9RB2YZhhLWre6iCXEWmDIsnhOHZr2deKvH+9BKmPAo6k46pCRWDynbsBzdkSTloFyR1SswqtXVxFLFq56ej1iK8oHaocyVM9dBokO4NU17OiI7L87lgaSqQyqQr5SH5olNwVd/MImIqLeZH03rN24C/FEGuFYCumMAV1TEfJ7hvSFZrEEu1IXews4sGVHOmOd+2g33lcKrLMqRVtbbqpvQWNzFKNHBPJjjc1RbKpvGfD7NpG0LnqTECiGAxwg21Qw3VRWOxQ3Y/lMB4jGk5Z9EqMx5+Wu575Ym1pjMMz9X6yb6p3ZHFVWo1wiInIvWd8N25rCaA0nsi2szGwrq9ZwAtvZ91jY8TMOsqyWefyMg0p9aK4n53yQ069DU5WCoFjpGhdRU+VHLJFGc1sMu1qiaG6LIZZIO7YdymDgSqIDtIaT0FQFhtm1kqhkC9e0hp0XJLptOZ53hoiIqDdZ3w0pm/7GyXRhelx/uCmDBwBWvd2A1z/YiUgshaDfg+NnHCSUuggAdaNCCPo9CHcrhBL0e1A3KlSUYy4mWSt+ssg4H3xe62I4Pq9Y03tNVQqeWxPiQeLYkUFs+Nve/M/ptIG2cAJjHdoSZjAwSHQIA2a+VLIJAEoRyjRJ4Lagq6bKj6bWwmMeyneGiIiGOlnfDXaVNkV6+blt28Sqtxuw6q2G/M+RzlT+Z5FAce3GXagM+lAZ9BWMO+15UFTAtLhfoAjm78kq7FlT5cfWHW0Id6ZgmCZURUGo3IPJ46oGPOfwijI0Nkctx0VE49b7Ou3G+6pxTwTVIV9BqvhQLiLJdFMH8Pu0bI/EbgxDrPSwLDVVfptxZwZdshrlEhGRe8n6bphQG0JVyAddVwEF0HUVVSGfUC8/t22beP2Dnf0a76vmthjaIwk07olge1MYjXsiaI8kHHmTuvc13ReNl5pHV9EeScIwTMAEDMNEeyQp1F7Ert2HaBsQq8qmBxrvq+a2GMp8Omqq/Bg9PICaKj/KfLoj31+DhSuJDiBrc68M86aP7nFHs/u4E8lqlEtERO4l67th3vTRaGqNwe/TC8YHym0ZPHZNzUWrkKbSBtq7BRiGmQ1kgg4sXCOLqgBWsZAquOTz8bZWKL3mVhUItReJ2rT7sBvvK1mpvDVVfmzbHS5YSZzgwHTmwcIg0QE6bUoidwouncvgxqBLRqNcIiJyNxnfDTK+I922bUJWFdL2SNIyOGiPOq9+w6ATzDftiCZhmj0DLdMEwgLPrV19GtEqpKFyDzos3l+hcrH3l9WexNZwAnMduggyGBgkOoBpc8bYjZcagy4iIqIvUpzvcLdl8Bw/46AeexK7j4uw7z0oVhTITewyKgUzLaEqCtIW71dFcV6pndHDA+jobCsc79a+YyAa90RQFfIh0m0lMTjE9yQySHQCm7VzJ56cRIPBbZX8iIgAOUVm3JbBkytO8/oHOxGNpRAoUnVTVVFQWNcymxbpNJqqWO6RE63AKYtqc1x2432hqwrSFs+Brok9B01tnZbjeyxW2/ujuS2bJt47Vdypad2DgUGiAwR8HoQtcvXLy/jy0NDjtkp+REQ58ttEOTPDqLfFc+qEg8Leyv062i1ag4mmscq4KVkd8mJve8JyXISswMuwWYq0G+8LxWYDpegCSIdNCmx7tPD57g+3pXUPBkYhDlAZ9Ozf6N1tVbEyMHQ2YxPluK0XJxFRjowiM5vqW/A/r2zNp8E1tcbQsDuMr58yeUh9Jk4eW2XZpuHLYysHPOem+hY8+crWfLGSptYYtu0O4wLB57bMqwMoDFqy4wNn2wJD8N6BYZqWhV9E0ljTGevii3bjfSWrcqystO5cz9BoPI1AmV6UVfXBwiDRATy6hoqgF5HcB5+qIFjugUfny0NDj9sq+RGRXG5KP5exGrF6XQPawvsDjlyT79XrGhz7PMgwb/poNOwOw+c18nvGvB5N6CJ+9bptaO313LaGE1j99jah57Y1nICuKTAMEyay9/9VVenxbw2ErPYPFQEv2iPJHvNoqoIKgcUKWYVrZJGR1t29Z6iiKEXrGTpYGIU4QE2VH/ssPjiG8hI3DV1M+SCiHLeln8tYjbBqSH6g8X9kyVQGiWQGhmkikzHhFejjBwCNzdZFSYZasZJDJlRj3f/b3WM10TBMHDKhumTHVArFLsx4oJ6hDBKpTzy6io5c7x8le2J2CDYxJXIrt1XyIyJ53JZ+7rYiM7LIWP1dvW4bOuNpaKoCrSuc6YynhVf9ZKgO+bCzWxBvAshkTFQP85XuoA4glTagawpSmf3LfB5NQSrtvH7dqmqdWipSZEcWWT1DB0tJgsQ//elP+OMf/4i7774bALBhwwbcdttt0DQN8+bNw+WXXw7DMHDzzTdjy5Yt8Hq9WL58OSZMmNCv33WLj7e1QuuelqBk3+wiTUyJ3IoXWUSU48b082KvRoytCaJ+V0fh+Mhg0f6NYpK1+itj1W9sTQD1u8KW4yICZTqUXsGMqmbHneijhtYeASIApDImPmoY+HWo36dZtifx+7QBzwkAVUEfWjsSPfZnKgCqgmJFgWQI+j3oiCYL0o4ryp13rFYG/d26fPlyrF27Foccckh+7KabbsJ9992HcePG4ZJLLsHmzZuxc+dOJJNJrFy5Ehs2bMCdd96Jhx56qF+/6xaRWAqqokDVFCiKku+P6JY7DUTFxl6cRAQw/RwAFh0zoUdxFV1TEfJ7sGiOM2+Gu2n1d9ExdT2KAuV64y06pk5o3rZoEioUQDGzTeoVQIWCtqgzr+s649bHZTfeF6cfPQHPvVlfsM/x9KPF3rejhpVjX0fPLVpm17jT5NJ4AQBKdj9mJuOeNN5BDxJnzpyJk046CStXrgQARCIRJJNJjB8/HgAwb948vP3222hubsaxxx4LADjiiCOwadOmfv2umwT9HkQ6C09E0bLOREREbsb08+xNswtOmeya7ApZq79jawL47POOglUZkVW/aROH4+sSnttU2oCqKtlAscd44cqaE9jVvREpMiOrX+bufZ1QlJ7HpijZcadJpQ3LwpROTOO1Ii1IfPrpp/HEE0/0GLv99tuxcOFCrF+/Pj8WiUQQDO5PmQgEAtixY0fBuKZp/frddDoN/QDVQWtqQkKPr5gWzZuEp/60Nf9zrofMonmTHHWcZI+vk7vw9XIfvmbuU4zX7ISaECory/GXd7Zj974oRg0L4MTZ4zFzysgiHKF7VO6LwefzQNeT8Pk8qKwsL/o5Uaz5xtZWYNfewhTQMSOCQv/G7MPG4NOdHfmAxgSgmNlxkXlPqAnhhNl1A/77Vvw+HdFY2mLcI+2zTGReXVMtW1Pomio07+FTatHcnsDulihGDQ/g8Cm1wo+/PZosCF5NM9s/0WnfE62RJGqq/Kip8vcYb3PgsVpRTHPwi9GuX78ev/vd73DPPfcgEong3HPPxYsvvggAeOKJJ5BOp7FnJE/sPgAAIABJREFUzx4cfvjhWLhwIQBg/vz5ePHFF/v8u2vWrBnsh0VEREREROR6JS+fGQwG4fF4sH37dpimibVr12LWrFmYOXNmPtDbsGEDJk+e3K/fJSIiIiIiov5zRJmlW265Bddccw0ymQzmzZuHww8/HIcddhjeeustnHfeeTBNE7fffnu/f5eIiIiIiIj6pyTppkRERERERORMJU83JSIiIiIiIudgkEhERERERER5DBKJiIiIiIgozxGFawgwDAM333wztmzZAq/Xi+XLl2PChAmlPiw6gLPPPhuhULbPzdixY3HHHXeU+IjIzocffoi77roLv/71r7Ft2zZcf/31UBQFX/7yl3HTTTdBVXm/zEm6v16bN2/Gt7/9bdTV1QEAzj///Hy7Iyq9VCqFG2+8ETt37kQymcRll12GL33pSzzHHMzqNRs1ahTPMwfLZDL4wQ9+gPr6emiahjvuuAOmafI8cyir1yscDrvuHGOQ6BB//vOfkUwmsXLlSmzYsAF33nknHnrooVIfFtlIJBIAgF//+tclPhL6Iv/1X/+F559/Hn5/tpntHXfcgauuugpf/epX8aMf/Qh/+ctfcPLJJ5f4KCmn9+v10Ucf4Rvf+AYuvvjiEh8ZWXn++edRVVWFn/zkJ2htbcXXvvY1fOUrX+E55mBWr9l3vvMdnmcO9tprrwEAfve732H9+vX5IJHnmTNZvV4LFixw3TnGWw4O8d577+HYY48FABxxxBHYtGlTiY+IDuSTTz5BLBbDxRdfjIsuuggbNmwo9SGRjfHjx+O+++7L/7x582bMnj0bADB//nysW7euVIdGFnq/Xps2bcLrr7+OCy64ADfeeCMikUgJj456O+200/Dd7343/7OmaTzHHM7qNeN55mwnnXQSbr31VgDA559/jhEjRvA8czCr18uN5xiDRIeIRCIIBoP5nzVNQzqdLuER0YGUlZVh6dKleOyxx/K9O/l6OdOpp54KXd+fNGGaJhRFAQAEAgGEw+FSHRpZ6P16TZ8+Hddddx2efPJJjBs3Dg888EAJj456CwQCCAaDiEQiuPLKK3HVVVfxHHM4q9eM55nz6bqOZcuW4dZbb8Wpp57K88zher9ebjzHGCQ6RDAYRDQazf9sGEaPCyVylokTJ+LMM8+EoiiYOHEiqqqq0NzcXOrDoj7ovmcjGo2ioqKihEdDX+Tkk0/GtGnT8v//o48+KvERUW+7du3CRRddhLPOOgtnnHEGzzEX6P2a8TxzhxUrVuDll1/GD3/4w/y2F4DnmVN1f73mzZvnunOMQaJDzJw5E2vWrAEAbNiwAZMnTy7xEdGBPPPMM7jzzjsBAE1NTYhEIqipqSnxUVFfHHrooVi/fj0AYM2aNZg1a1aJj4gOZOnSpdi4cSMA4O2338bUqVNLfETU3d69e3HxxRfj2muvxT//8z8D4DnmdFavGc8zZ/vf//1fPPzwwwAAv98PRVEwbdo0nmcOZfV6XX755a47xxTTNM1SHwTtr266detWmKaJ22+/HQcffHCpD4tsJJNJ3HDDDfj888+hKAquueYazJw5s9SHRTYaGxvxve99D0899RTq6+vxwx/+EKlUCpMmTcLy5cuhaVqpD5G66f56bd68Gbfeeis8Hg9GjBiBW2+9tUdqPpXW8uXL8dJLL2HSpEn5se9///tYvnw5zzGHsnrNrrrqKvzkJz/heeZQnZ2duOGGG7B3716k02l861vfwsEHH8zvMoeyer1Gjx7tuu8yBolERERERESUx3RTIiIiIiIiymOQSERERERERHkMEomIiIiIiCiPQSIRERERERHlMUgkIiIiIiKiPAaJREREgrZu3YopU6bg5Zdf7jH+9ttv4+tf/zpOPfVUnHzyybjyyiuxe/fu/J9PmTIFQLbtx7Rp03DWWWflG5wvWLAA9957b4/5IpEIFi9ejMbGRvkPioiIhiy91AdARETkds8++yxOO+00rFy5EqeeeioA4N1338W1116L+++/H0cccQQA4Mknn8R3vvMdPPvsswVzjBw5Es8991z+56amJpx66qlYtGgRDj74YHz44Yf4wQ9+gIaGhkF5TERENHRxJZGIiEhAKpXCCy+8gKuuugqbN2/G9u3bAQAPPvggLrvssnyACAAXXHABFi5ciGQy+YXzNjc3wzRNBAIBAMBTTz2Fm266CSNHjpTzQIiIiLpwJZGIiEjAG2+8gTFjxmDixIk46aSTsHLlSlx77bXYsGEDrr/++oLfX7p0qeU8e/bswVlnnYVEIoHW1lYcdthhuP/++zFq1CgAwG233Sb1cRAREeVwJZGIiEjAs88+i8WLFwMAFi5ciN///vf5lUJFUQAAyWQyv9/w+OOPx/vvv18wTy7d9MUXX8RZZ50F0zQxd+7cwXsgREREXRgkEhERDVBLSwvefPNNPP7441iwYAF+8IMfoKOjA3/6059w2GGH5YNBr9eL5557Ds899xzGjRuHVCplO6eqqrjuuuvQ1NSExx57bLAeChERUR6DRCIiogF67rnncPTRR2PNmjV49dVX8dprr+Hb3/42fve73+GKK67AAw88gA8//DD/+5988gl27NgBTdMOOK+u67juuuvw4IMPorm5WfbDICIi6oF7EomIiAboD3/4A66++uoeYxdccAEeffRRVFdX45577sHPfvYz7N27F52dnRg9ejSWLVuGWbNmfeHc8+fPx4wZM/Dzn/8cy5cvl/UQiIiICiimaZqlPggiIiIiIiJyBqabEhERERERUR6DRCIiIiIiIspjkEhERERERER5DBKJiIiIiIgoj0EiERERERER5TFIJCIiIiIiojwGiURERERERJTHIJGIiIiIiIjyGCQSERERERFRHoNEIiIiIiIiymOQSERERERERHkMEomIiIiIiCiPQSIRERERERHlMUgkIiIiIiKiPAaJRERERERElMcgkYiIiIiIiPIYJBIREZWYaZqlPgQiIqI8BolEROQ4F154IaZMmYIzzjjD9nceffRRTJkyBQsWLMiPXX/99ZgyZQqef/55y79z1113YcqUKfmff//732PKlCn47LPPinfwB7B+/XpMmTIFa9asAQDE43EsX74cL7zwgvR/e926dbjssstwzDHHYNq0aViwYAFuuOEGfPzxxwW/e+GFF+Lcc8/9wjnj8Th+8Ytf4Mwzz8Thhx+OGTNm4KyzzsJDDz2EWCwm42EQEdEgYJBIRESOpKoqtm7dir/97W+Wf75q1Srbv3vrrbeiqalJ1qEN2NSpU7Fy5UrMmDEDALBz5078+te/RjqdlvrvrlixAt/4xjegqip+8IMf4PHHH8fll1+O+vp6nHPOOfjNb37T7zlN08Sll16KJ554Ih8Y/vznP8eJJ56IRx55BBdffDEymYyER0NERLLppT4AIiIiK1OmTEFjYyNWr16Nq666qsefffbZZ/j4449x6KGHor29vcef+Xw+xONx3HjjjXjssccG85C/UDAYxBFHHCE0x/XXX58PLvti5cqVePzxx3HLLbfgvPPOy4/Pnj0bZ599Nm6++Wbceuut+NKXvoTZs2f3+Tjee+89/N///R8efPBBnHjiifnx+fPnY/z48Vi2bBlee+01nHTSSX1/cERE5AhcSSQiIkfyer04+eST8dJLLxX82apVqzBt2jTU1dUV/FkoFMJVV12FtWvXDmiFzEoymcQjjzyChQsXYvr06ViwYAHuueceJJPJHr/3wgsv4IwzzsBhhx2G0047DS+99BJOPvlk3HfffQB6ppuuX78eCxcuBADccMMNPdJmi8UwDNx///045phjegSIOaqq4vvf/z5qamryx9hXzc3NAKz3U55yyim46qqrMGbMmIEdOBERlRSDRCIicqxFixahoaEBmzdv7jG+evXqA+5X/MY3voFZs2bhJz/5CbZv3y50DKZp4rLLLsMDDzyAM888Ew899BCWLFmCxx9/HN/5znfyQdILL7yAa665BlOmTMEDDzyA8847D9///vexa9cuy3mnTp2Ke+65BwBw2WWX4f7777c9hnQ6nf/PNE2YptljzM7HH3+MPXv2HHA1z+fz4ZRTTsFf//pXtLW19eUpAZBdiQwEArjuuutw2223Ye3atYhEIgCA8vJyXHbZZTj00EP7PB8RETkH002JiMix5syZg2HDhmH16tWYOnUqAGDjxo1obGzEokWL8OGHH1r+PVVVceedd+LMM8/EsmXL8OSTT0JVB3Zf9M0338TatWuxfPlynHPOOQCAuXPnYvjw4bjpppuwZs0aHHfccfjZz36GOXPm4K677gKQTbscNmwYrr32Wst5g8FgvojO+PHjDxhQ5R673diWLVss/96OHTsAAGPHjj3gY5wwYQJM08Tnn3+OqqqqA/5uzvDhw/Hoo4/ihhtuwK9+9Sv86le/gqqqOPTQQ3HKKafgggsuQDAY7NNcRETkLFxJJCIix9I0Daeddhr++Mc/5lfsVq1ahaOPPho1NTUH/Lvjxo3DsmXL8P777+PRRx8d8DGsX78eAApWLs8+++z8n2/fvh2NjY359NGchQsXQtO0Af/bOc8880z+vxNOOAFTp07tMWYn95x90THo+sDuGc+cORMvvfQSfvvb3+KKK67AV7/6VXz66af46U9/ikWLFuWDVCIicheuJBIRkaMtWrQIv/nNb7BhwwYcfvjheOmll3D11Vf36e+ed955+POf/4x7770Xxx133ID+/fb2doRCIZSVlfUYLysrQygUQjgcxr59+wAAw4YN6/E7uq6jurp6QP9ud4cddlj+/1dVVSEajfYYs5NbQWxsbDzg7+VSckePHt3vY1NVFTNnzsTMmTMBAIlEAr/97W+xYsUK3HXXXfj5z3/e7zmJiKi0uJJIRESOduSRR2LMmDF48cUX8c4776C9vR2nnHJKn//+bbfdhvLyclx33XVIpVL9/vcrKysRDocRj8d7jHd2diIcDqO6uhqjRo0CALS0tPT4nUwm0699fsU2depUjB49Gi+++KLt76TTabzyyiuYNWtWvwLaq6++2rIYjs/nw7//+7/jmGOOwaeffjqg4yYiotJikEhERI6mKApOP/10vPLKK1i9ejVOOOGEfu11q62txQ9/+EN88sknePbZZ/v973/1q18FgIKG988//zwA4KijjkJtbS3q6urw8ssv9/idv/zlLwcsLFOMVNQDUVUVV155JdavX4///u//tvydFStWYOfOnfiP//iPfs09YcIEfPDBB1i3bl3Bn6VSKTQ2Nub3XBIRkbsw3ZSIiBxv8eLFeOyxx/CHP/wBP/vZz/r998844wz86U9/Kgjicp577rmCVFEA+NrXvoZjjz0WxxxzDJYvX46WlhZMnz4dH374IR566CHMnTsXc+fOhaIouPrqq/Hd734XN9xwAxYuXIjt27fj3nvvBZANdK1UVFQAAN5++20cfPDBOPzww7/wsdx55519fdgAgH/6p39CfX097rjjDrzzzjs444wzUFNTg88//xxPP/003n//fdx4442YO3duj7+3d+9ey8By5MiRWLhwIZYuXYpXX30Vl156Kf7lX/4Fc+fORSgUwo4dO/Db3/4WbW1tuPLKK/t1rERE5AwMEomIyPEOPfRQTJw4Efv27cP8+fMHNMfNN9+M999/P9/fr7uHH37Y8u8ce+yxqKysxEMPPYT77rsPK1euxP33349Ro0bhm9/8Jr797W/nq6aedtppWLFiBR5++GG88MILGD9+PH784x/jyiuvRCAQsJx/2LBhuPDCC/Hss/+fvfuPbqu87wf+vldXkmVLiRSjOAkmcUIJa3FNEkIoYAiUX4WwQpvya4Wtgy5jK2x0kPHjtITyI6Hr0v2AQtaermUtZwVKOzhJv21OQwN1SAuEZKkzGqC1HWIcRzhSIsmypKt7v384UmRLCo7vfaT7RO/XOTurbpWnj+/Vj/vR5/N8nuexefNmbNmyBR6PZ1J/39HceeedOPfcc/H000/j0UcfxYEDBxAOh3HWWWfh3nvvLdtZtb+/H2vWrCk5fvrpp+OKK65AIBDAf//3f+P73/8+Nm3ahJ/+9KdIp9MIh8Po7OzEv/7rv3KfRCIiSSlmuV1wiYiI6JisX78eH/3oR3HyyScXjr3zzju48sorsW7dOlx44YU1nB0REdHEMUgkIiKywV//9V/j97//Pb785S+jtbUVAwMDWLduHRRFwU9+8hMhGUIiIiIRahIk/u///i/++Z//GT/4wQ/Q19eHe+65B4qi4JRTTsGqVaugqioef/xxbN68GZqm4b777kNHR8cxPZeIiKiaYrEYvvnNb+Lll1/G0NAQQqEQLrjgAnz5y18uu96RiIjIqaq+JvE73/kOXnzxRfh8PgDAmjVrcMcdd+Css87C/fffj02bNmHWrFl47bXX8Nxzz2FgYAC33347nn/++WN6LhERUTUFg0E8+OCDtZ4GERGRZVXfAmP27Nl47LHHCo937dqFJUuWAADOP/98vPrqq9i2bRs6OzuhKApmzZqFXC6HAwcOHNNziYiIiIiI6NhVPZN42WWXYe/evYXHpmkWWoM3NTUhHo8jkUggGAwWnpM/fizP/bDSHl3PQdPE7k9FRERE5ERv7t6PH/zs/0qO33TFx7Do1Ok1mNHx5c3d+7HptT3YdyCJGdOacNGS2XV1Xv/pB29g4INEyfFZJ/ix8qbFNZgRHauab4GRbx0OAMlkElOmTIHf70cymRxzPBAIHNNzP0w0OmzTX2CP7p4hdO0cQDSRQcjvQWfHTLTPba71tGgCwuEAIpF4radBE8TrJR9eM/nwmjnfSdN8+PS5bejaOYBYMoNg0+i9x0nTfI69dvl7pUgshXDQ5+h7pYMHhzGSziKbzWEkncXBg8O2nlenv8f2Dh6CUabryXuDcUfPWxQnX69wuHzcVPVy0/E+9rGP4be//S0A4JVXXsHixYuxaNEidHV1wTAMvP/++zAMA9OmTTum58qku2cIz7/8RwxGUzBNE4PRFJ5/+Y/o7hmq9dSIiGqmu2cI617oxj/868tY90I3PxOJbNY+txm3XtWOtX+/FLde1e7YgAsYe69kmHD0vZJMcxUlHPRVON5Q5ZnQZNU8k3j33Xfjq1/9Kr75zW9i3rx5uOyyy+ByubB48WJcd911MAwD999//zE/VyZdOwcqHnfyBzYRkSj5mywAcGtq4SYLAD8XiepQ184BpNI6Eqks9JwBzaXC73M78l6J93VAZ8fMwmf2+OMkh7rdJ9FJKd+Hnnq9kJJ3ayqyugEAUBUFX/0L1m07nZNLCKgUr5cc1r3QjcFoCsDYz8WWkA+3XtVey6nRBPB9Jhe7r5eIstB7v70V0UPpkuOhKQ1Ys+ITlsa2W/F9XTE77+tkeI8deR2MIBxssK08eP3WXmze3o9EKgu/z40LFp6IK89uszyuSE6+XpXKTWueSaTRlHz+Zmjscabkiag+RWKln4mjx0eqPBMiOhbFVQAAbKsCyOoGDMOEYZowTUBRRoOurJ6zPGe78b5uVPvcZtszp+u39mL9lt7C48RwtvDY6YGibGq+JpEqp96ZkieiesX1LERyOlqppRWGaSJnjAaIAGCaGPPYSXhfJ87m7f3HdJwmj5lEB8j/ypLvMNYScnbHLiIi0biehUhOoqoAVEWBy6XAMEyYABQAqqrg8M5ojlJ8X2d3qWW9S6SyZY8nKxynyWOQ6BD5lLyTa5aJiKqFP54RiSdi+y1RpZZurXzxm8ehe16LKLUkwO9zIzFcGhA2+dw1mM3xjUEiERE5En88E0em/eZIjO6eITy98W3EU1nkcib6XQr69sXx+UvnW3otiKoCCDZ5MXSwNBs51e+xNC7J5YKFJ45Zk1h8nOzFIJGIiKiOiGosQnLZ8GofovHRbqGKokDXDUTjaWzY2mfpdSCu1NKEqihQXePqS524KBHy/RAjy3zzzWk2b+9HMpVFkyTdTWXEIJGIiKiOcA83AoC9kcSRbqE4vMZPUbB3f8Ly2CJKLTO6gWDAW7JPYkZ3XpBYnKXVcwYGoylbsrSiyPbD0ZVntzEorAJ2NyUiIqoj3F6EAEDPGWW7heo5o7YTq0Cmjsf5LK2uG4CJMVlaJxLVkZbkxiCRiIiojsh0s03iVGr44nE7sxFM63Q/YuMCr1g8jdbp/lpPrcTeSPlsrB1ZWhH4wxGVwyCRiIiojnAPNwKARp8Gl+vIFhKKArhcCpoanNklcu/+BEIBLzRNBRRA01SEAl7HBl4y4Q9HVA7XJBIREdUR7uFGADCnJQCYGO1uaphwqQoCPjdmtzgvMweMZrsavBoavNq4487LdrWGm9AzUNqRuTXcVIPZfDjuS0vlMEgkIiKqM9zDjTo7ZmIwOhp4uTUVWd0oHHciUfsvirDsnDZ8d8NbSAxnYZijXVn9jW4sO6fN8tgi9rbkD0dUDoNEIiIiIgcTsT1BcWAQS2bQErJv2wMR85Ut26V8yOPJKO5C6tZUW7uQ8ocjGo9BIhEREZFDidyeIB8YhMMBRCKl5ZGTIWq+MmW7Nrzah+ERHS5VgetweDg8olveg5Lb11A1MUgkIiKySJaNqEk+sgUGIucrS7ZLVHfTSCyFkbQ+uo40Z8LlGl1H6sR1mSQ/BolEREQWyLYRNclFtu0JZJuvTD/weDQX+uNJAICiKIX9F4MBb41nVp6ocyvTNZMZt8AgIiKygBtRk0jhoA8jaR2RWAoDQ8lCNsmJDVsAubZTyP/AMxhNwTCP/MDT3TNkadxKXUytdzc1KxyucLyGRJ1bUeNSKQaJREREFsiWOSG5tE73IzpuE/moQzeRB0YbyZQLap3YYEbUDzzLzmlDcNyejsGA13J304xuwNegIWeYyOg55AwTvgYNGd15QaKoc9u1cwCpca+vVFrnj3ICsNyUiIjIApla85N89u5PIBjwIpHKQs8Z0Fwq/D63ozeRHx+yOC+EGSXqB572uc3o7JiJzdv7kUgZaPC4bCmJ9GgqUocb4miKCtM0kRrR4QlZ751qdwmnqHPbNxhHLJ4uPNZ1A7F4Gn2KHf1jqRgziURERBZUypA4MXNC8onEUvB5NYSDPsxsbkI46IPPqzk2Uy1T+bWo0tjuniFs2x1BoNGDmc1NCDR6sG13xIaSyAqBkMUASUQJp6hzm9/Ps/R4ztK4VIpBIhERkQXtc5uxfOk8tIR8UBUFLSEfli+dx0YKZAuZ1vgBRzI9xeWxsXgafYPOy3yK+oFHVKCc0XMIjStjDQW8yGTLB04TJWK+os6tWysfung0l6VxqRTLTYmIiCySpTU/yUfkJvL5EsNoIoOQ32NLSaRMmR5Rey+KKrXMl7Y3eDW4NbVwrq3+YCBivqLO7ZyWAGAC8aLy64DPjdkt1tfoiuiaKuI9Vi0MEomIiIgcStTNdnfPEJ7e+HZhz71+l4K+fXF8/tL5lsaWLdMj4gceUeuURf1gIGq+Is5tZ8dM9O2Llz1uhYitjIrHdGuqdNsjMUgkIiIicjARN9sbXu3D0KERGIYJE4CiA5lsDhu29ln63xKZ6ZGFqGCu+AeDWDKDlpA92S6R2WoRRDRGOlrJ7WTPr4gxq4lBIhEREVGd6RuMI5c7fHutjG61l8uZZbM0x0JUpkcmorK/+bHb5zYjHA4gErF2rYrHBMTM125dOwfg82rwebWS407rxir79kgMEomIiIjqTOW1g9aaoADybIEhkmzrlGWZr+j1nqXHJ19yK/v2SAwSiYiIiOqM5lKQMUrDN81lbTsFUZke2YhoglI8rgyNUEScA5nWe8pWxjseg0QiBxH1pUJERFSsbUYAf+g/BMM8vCZRAVRFQduMgKVxRZbYyfIdKaIJyvhxnd4IRdQ56OyYiR9ufBuJojWvfp/b1vWedpXcilpDWi0MEokcQtQHKhER0XjLzmkr3GznciZcLgV+nxvLzmmzNK6oTI9M35GiGpZ07RxAKq2XXDMnZmlFNm0Zn+u2lvs+QkTJrYg1pNXCIJHIIWTvgkVERPJon9uMGy+dX8hyBJvsKV0UVWIn03ekqGxq32AcB8p0pFUUu8Ik+0RiqUJAW5zxs3oOunYOoMGroaHOy5mrgUEikUPI3gWLiIjkIlOnTJm+I0VlU4dTetmOtMMjWUvjiuDRVPTH04XHum4gFk8j5PdYGlem14HsGCQSOYTsXbCIiIgAuTaoF0FUNjWbE9eR1n4VspsWs54yvQ5kp9Z6AgDwk5/8BDfddBNuuukmXHvttfj4xz+OjRs34uKLLy4cf+2112AYBu6//35cd911uOmmm9DX1wcA2LFjB6655hpcf/31ePzxx2v81xBNTqUvD1m6YBEREYki03dk+9xmLF86Dy0hH1RFQUvIh+VL51kOnF2qApdLKcRZigK4XApcqvPKTTN6DqGAF5qmAgqgaSpCAS8yWWsBrUyvA9k5IpP42c9+Fp/97GcBAF/72tewfPly7Nq1CytXrsRll11WeN7GjRuRyWTwzDPPYMeOHXj00Ufx5JNPYtWqVXjsscdw0kknYcWKFdi1axdOO+20Wv05RJMi02a2RERE1STbd6SIbGpruAk9A3GoLgWKosA0zcJxp8ln/MavHbSa8ZPtdSAzRwSJeb/73e/w7rvvYtWqVfjiF7+It956C0899RQ6Ojpw1113Ydu2bTjvvPMAAAsWLEB3dzcSiQQymQxmz54NAOjs7MTWrVsZJJKUZNnMloiIqNrq/TtyfEdaTVNt6Ugrgsg9AkW9DmTZYqVaHBUk/sd//Ae+9KUvAQDOPfdcXHzxxWhtbcWqVavwox/9CIlEAn6/v/B8l8tVcqypqQnvvffeh/5vhUKN0DSX/X+EDcJha3sUUfXxmsmF10s+vGby4TWTC6+X810YDmDq1EZsem0P9h1IYsa0Jly0ZDYWnTq91lMrIdNcAeDN3fvx4pZeAIDLpeJAPI0Xt/Ri6tRG2+Ys23vMMUHioUPxVcaLAAAgAElEQVSH8Mc//hGf+MQnAADLly/HlClTAAAXXXQRfvGLXyAQCCCZTBb+jWEY8Pv9Y44lk8nCvzuaaHTY5r/AHjLuo1LveM3kwuslH14z+fCayYXXSx4HDw5jJJ2FaQIj6SwOHhx27LXLzzWbzdk6VxEZvw2//kPZBkAbfv0HnDTNZ2lswNnvsUrBqyMa1wDA66+/jnPOOQcAYJomPv3pT2Pfvn0AUCgfXbRoEV555RUAo81q5s+fD7/fD7fbjT179sA0TXR1dWHx4sU1+zuIiIiIiOzW3TOEpze+je6eA9izL47ungOHHw/ZMva6F7rx0FOvY90L3ZbH7O4ZwvMv/xGD0RQMExiMpvD8y3907LjcWqOUYzKJPT09aG1tBQAoioKHH34Yt912GxoaGnDyySfj2muvhcvlwpYtW3D99dfDNE2sXr0awGizm7vuugu5XA6dnZ04/fTTa/mnEBEREVEdE5LterUP0cN7DyqKAl03EI2nsWFrn6Wx84FXXj7wAjDpcbt2DlQ8bmWuosbl1hqlHBMkfvGLXxzzuLOzE52dnSXPe/DBB0uOLViwAM8++6ywuRERERERTYSIoAsA9kYS5Y/vL398okQEXqIyc6LGFdloR1aOCRKJiIiIZMcOieLOgYhxRYwpKtsFAIZpwjBMmBjdrl61YY9EEYGXqMycqHG5tUYpBolERERENhCVQZIp8BR5DuweV9RcRWW7QgEv+iOHmzUqgGkCuZyJ0DSvpXFFBF6iMnMybq0hK8c0riEiIiKS2dEySJMlqlGHKCLOgahxRc01HCzfDdNqtqupQYNLVaAcTh4qCuBSFTQ1WMv5VAqwrARe7XObsXzpPLSEfFAVBS0hH5YvnWc5CBM1LpViJpGIiIjIBiIySCJLF0WQaS2abOvbMrqBaVMbkEhlkcuZcLkU+H1uZHTT0rjtc5vRuy+Ozdv7kUhl4fe5ccHCE20J6ES8Rpnxqw4GiUREREQ2EFG2J1trfpFr0fr2xRFPZaHnDGguFQGfG3NmTH6DctnWt4WDPhjRFHxeDW5NLezrZ3W+3T1D2LY7gkCjB4FGDwBg2+4I2mYEGIzVMZabEhEREdlARNmeqNJFUUScAwBone5HNJ6GrhuAicL2D63T/ZMeU9RcgdFA8dar2vHVv1iMW69qtyXYEjXfrp0DSKV1RGIpDAwlEYmlkErrlstuSW7MJBIRERHZQEQGSbbW/KKyaHv3JxAMeJEoyiT6fW5L2z/I1tGyeL6xZAYtIXuaGPUNxhE7vP8iMBqAx+Jp9CnWO6eKIFMjJ5kxSCQiIiKyid3rpWQLZAAxa8ZEld3Ktr4tP99wOIBIJG7LmPmy1dLjOVvGt1N3zxCe3vh2oex4MJpC3744Pn/pfKmuowwYJBIRERE5mGyBjAgeTUV/mWxXyO+p4ayOD26t/Oozj+aq8kw+3IZX+zB0cASGacI8XHacyeSwYWtf3b9H7MYgkYiIiIgcrkLpI0siLZvTEgBMlDQFmt0y+fWeovTuO4SccaSbq2kCOdNE78ChGs7q+MQgkYiIiIgcLaPnEAp4SwKZTLZ8qWQt5fe2zMvvbQnAkYFiZ8dMDEZTaPBqJcedRs+V3+6j0nGaPAaJRERERORo+e0qxgcyTuzyKtveljKte3VrKtKZ0rWSlUpmafIYJBIRERGRo8nU5VW2vS0Beda9zmkJ4A/vH4RhmDAxWoSsqoql/TKpPAaJRERUV2RaK0REo2TKduWznqXHnZf1lM2yc+aM6W6aLztedvacWk/tuMMg0SHyNy3RRAYhv8exH3xERDKTba0QER0hS7ZLZNaz3u8X2+c24/OXzpfixwLZMUh0gOKbFrem8qaFiEgQ2dYKEZF8RGU9Rd4vylRhIcuPBbJjkOgAvGkhIqoOGdcK1TuZbl6J8kQEMqLuF1lhQeUwSHQA3rQQEVUH1wrJhTevcmJgL+YcRGIpjKR1xFNZ5HImXC4FAZ/b8v0ikxVUDoNEB+BNCxFRdcjUIZF48yojBvaj5+CHG99G4nBzlcFoCr374rjx0vmWzoFHc6E/ngQAKIoCXTcQjacRDHgtzVe2ZAV/hKgOBokOwJsWIqLqkKlDIsl380piA3tZgoMNr/YiFk8XHuu6gVg8jQ2v9lqcrwnDMGGYRds/KApgWttIXqZkBX+EqB4GiQ5QfNMSS2bQEnLuBx8RkezY9EAeMt280ihRgb2o7JyIwHNvJHlMxycqlsyMRobFMaECxJJZS+PKlKxgdUH1MEh0iPxNSzgcQCQSr/V0iIiIak6mm1caFQ760LcvXrKPndXNzkVk52TLSmV1A6qiQHUpUBQF5uEMYlbPWRpXpgoLVhdUD4NEIiIih5KlvE4UmW5eaVTrdD92vPNB4XF+3dy5FgP7vZEkDHO03LJQaqkqlrJzorJSrWE/egYOlR6f7p/0mMDothflzoFHc1kaF5CnwoLVBdXDIJGIiMiBZMtyiCLLzSuN2rs/gWDAWygL1Vwq/D439u5PWBo3Z5jQc0fqLE0ARs6E5pr8ejxRWall58zB0xvfLsmmLjt7jqVxg01eDB0sndtUv8fSuDJhdUH1MEh0iPVbe7F5ez+SIzqaGjRcsPBEXHl2W62nRURENcK1NySjSCwFn1eDz6uNO24t8FKUYzs+EaKyUu1zm/H5S+cLyICbZctNrTaukQmrC6qHQaIDrN/ai/VbegGMtjRODGcLjxkoEhHVJ669IRmJCrwMo3wgVOn4RIjMSonIgGd0o5ClzeVMaNpoljaj10+QCLC6oFrUWk+AgM3b+2EYJvScgYyeg54zYBgmNm/vr/XUiIioRsJBX4XjXHtDzlUpwLIaeGkuFZqqQFXyWz8AmqpAc03+VrZ9bjOWL52HlpAPqqKgJeTD8qXzHBuAhIM++LwawkEfTmrxFz3mZwLZj5lEBziUzCCX/yXs8HY3OdNEPJmp7cSIiKhmuPZmVL0375GNqHLAfDMYFWPrS602gznC+dk4fiZQNTFIdABVUZAr8+GkWCm0JyIiqXHtDZv3yEpEOaCIZjCyvb64rzZVE4NEB2jyucfs/VN8nIiI6le9r71h8x7KE9EMRuTrS1QGXKZ9tVkFIDcGiQ5wSutUvP1eDPHhLAzThKoqCDS6cUrr1FpPjYiIqGbYvIeK2f2jiajXl8gMZT7wiiYyCPk9jg28ZMvSUik2rnGAzo6ZmOr3onW6HyefOBWt0/2Y6veyxpyIiOoam/eQSKJeX0fLUFqRD7wGoymYplkIvLp7hiyNK4Koc0DV45hM4tVXX41AIAAAaG1txXXXXYdHHnkELpcLnZ2duO2222AYBh544AHs3r0bHo8HDz/8MObMmYMdO3aUPFcmrDEnIiIqxUYdJJKo15eoDKVM5desApCfI4LEdHp0Pd4PfvCDwrGrrroKjz32GE466SSsWLECu3btQn9/PzKZDJ555hns2LEDjz76KJ588kmsWrWq5LmnnXZarf6cSZGpxpyIiKga2LyHRBL1+goHfejbFy9psjNnRsDSuDIFXqL2y6TqcUSQ+Pvf/x6pVAo333wzdF3H7bffjkwmg9mzZwMAOjs7sXXrVkQiEZx33nkAgAULFqC7uxuJRKLsc2ULEomIiKhUvTfvIbFEvL5ap/ux450PCo913UA0nsa5FjOUxcFnLmfC5VJsCT5FYBWA/BwRJDY0NOCWW27BNddcg97eXvzVX/0VpkyZUvjvm5qa8N577yGRSMDvP7IfjsvlKjmWf+6HCYUaoWkue/8Qm4TDznuz09HxmsmF10s+vGby4TVzvmc3vY3/92ov4sMZBBo9uPycNlx70fxaT0t6kYNpnBBswKFkFlndgFtTMaXJjQ8Opi29L06d24z/fffI+sNczkQskcGlhyvRnOTCcABTpzZi02t7sO9AEjOmNeGiJbOx6NTptZ5azTjtGn0YRwSJc+fOxZw5c6AoCubOnYtAIIBYLFb475PJJKZMmYKRkREkk8nCccMw4Pf7xxzLP/fDRKPD9v4RNmG5qXx4zeTC6yUfXjP58Jo53/qtvVi/pRfA6L7MhxJpPLNxN5LJNK48u62WU6tIli0V9g4egltzoXnq2GTEe4NxS++L3T1DmOr3IFGUSfT73NjdM+TI99tJ03z4wqdOHXPMifOsBid/JlYKXh3R3fTHP/4xHn30UQDA4OAgUqkUGhsbsWfPHpimia6uLixevBiLFi3CK6+8AgDYsWMH5s+fD7/fD7fbXfJcIiIiIipv8/b+Yzpea8WdPQ0Tju7sKapraiSWgs+rIRz04aQWP8JBH3xezZFrEoHRa7buhW489NTrWPdCtyOvFVXmiEzi5z73Odx777244YYboCgKVq9eDVVVcddddyGXy6GzsxOnn346Pv7xj2PLli24/vrrYZomVq9eDQD42te+VvJcIiIiIiovkcqWPZ6scLzWZOrs2dkxEz/c+DYSRY1r/D635fV4MjWD4T6J8nNEkOjxeLB27dqS488+++yYx6qq4sEHHyx53oIFC0qeS0RERETl+X1uJIZLA8Imn7sGs/lwMnX2BADlQx5PhkzNYGQK6qk8RwSJRERERFSeiLV4Fyw8sbAmcfxxJ5Ipi9a1cwANXg0NXq3kuJXrJtO+2pFYCiNpvWQbEKcG9VSKQSIRERGRQ4kq28s3p9m8vR/DIzqafG5csPBExzat6eyYiac3vl0SdDgxiyYy6ynLvtoezYX++JHGkvltQIIBbw1nRceCQSIREVkiS8dBomKyvG5Flu1deXYbrjy7zfaAQ9S5NT/ksVPIlPUUp8LVMZ161Wg8BolERDRpbE5AMpLpdSvbWjxR57Zr5wB8Xg0+m0s4RZBp7aAoGd1AY4OG+HAWhmlCVRQEGt3I6AwSZeGILTCIiEhOR8tyEDmVTK9bUdspiCLq3MoULLfPbcbypfPQEvJBVRS0hHxYvnSe44JZkTyaC8MjOlyqArdLhUtVMDyiw+Nm6CELZhKJiGjSZLpxI8qT6XUrW1ZK1LmVrYQzv3awfokrN5WlVFx2DBKJiGjSZLtxIwLket0Wd7SMxEYQDjY4+qZY1LmVLViu90AmoxvwNWhIFJWb+m0oN5WpVFx2DBIdIv9hEk1kEPJ76u7DhIjkJNuNGxEg3+tWpqyUqHMrU7DMQAbwaCpSh8tNXYd3iUyN6PCErO0Yyf0Xq4dBogMUf5i4NbUuP0yISE4y3bgR5fF1O0rED9Qiz60swTIDGQCoEAwq1oJEmUrFZccg0QH4YUJEMpPlxo2oWL2/bkX+QF3v55aBDJDRcwgFvCX7WmayhqVxZSoVlx1bDDkAP0yIiIiommTq8Cob2TrSihAO+tDg1RAO+jCzuanosfW1qcdynCaPmUQH4K8iRERExwdZGpbI+AO1LOdWtjWvInBtqvwYJDoAP0yIiIjkJ1PDEtl+oJbp3DKQ4drU4wGDRAcofiPFkhm0hJz76xgRERGVJ1OPAdl+oBZ1bkVlJ2ULZEScB9nOAY3FINEh8m+kcDiASCRe6+kQERHRMZKphFO2H6hFnFuZspMi8TxQOQwSiYiIiGwgWwmnTD9Qizi3MmV+ReJ5oHIYJBIRERHZQFQJp6iSSBH7JIoi4tzKlPkVKRJL4WAijfhwFoZpQlUUBBrdUC3uaShLoyEqj0EiERERkQ1ENOsQVQoocp9EEUScW5GZX5kCpKxu4GAiU3hsmCYOJjLw+9yTHpMlrPJjkEhERERkE7ubdYgqBezaOYCRtI54KotczoTLpSDgc9tSYihLM5jOjpn44ca3kSja8N3vc9uS+ZUpQCoOEMccT5Y/PhEsYZUfg0QiInIkmUrhiEQRVRLZNxhHNJ4GACiKAl03EI2nodhQYihTgDT+r7X2148qDsDzwaddAfh3N/wfXn9rP7I5A26XijM/Oh23LPuYpTHTeg4ulwLDMGFi9ByoqoJMNjfpMWUs5ZUp+1sNDBKJiMhxZCuFIxJFVElkVjfKHs/okw8MALkySF07B9Dg1dDg1UqOW5lrcQAOwLYA/Lsb/g+v/m7f6ANl9BrmH1sJFP0+NxLDWaiusfNrslBuKlsTJ9l+3KgGtdYTICIiGu9oN5pE9aRS6aPVkki3Vv4W0K25LI0rUwZJ1FxFBeCvv7X/mI5P1AULTzym4xPR2TETqbSOSCyFgaEkIrEUUmldyn046xUziURE5Dgy3WgSiSSiYQsAzGkJwDSBxOE1iZo2uh5vTovf0rgyZZBEzVVUAJ7NlQ8+Kx2fqCvPbgMAbN7ej2QqiyafGxcsPLFwfLJElPKKwu+cUgwSiYjIcWS60SQSze6GLcBopmcwmoLPq8GtqYXsl9VMj6htQEQQNdfiALy4IY7VANztUstmKd0u64WBV57dZjkoLCaqlFcUfueUYpBIRESOI9ONJpGMijOUsWQGLSF7GnWIynwC9jcWETXX4gB8/HErzvzodGzJr0k0xx53Gtkyc/zOKcUgkYiIHEfUDSwRHZHPUIbDAUQicdvHtZOoxiIi5ioq+DzrYy3Y8c4HGB7RC11IGxs0nPWxFuuTtplsmTmRP27IikEiERE5kqgbWCKSj0xdUwExwWfXzgGcEPQBwJgSYSeeAxkzcyKumcwYJBIRERGRo4kqXxS1N56IcWUq4WRmTn4MEomIiIjI0USUL4oqYRU1rowlnAwK5cV9EomIiIjI0UTsFylqb7yunQMYGbdH4EhatzyuqD0zicphJpGIiIiIHE1E+aKo8s2+wTii8XThsa4biMbTUBRrOwWyoRdVE4NEIiIiInI8u8sXRZVvltvLEAAyes7SuAAbelH1OCJIzGazuO+++9Df349MJoO/+Zu/wYwZM3Drrbeira0NAHDDDTfgiiuuwOOPP47NmzdD0zTcd9996OjoQF9fH+655x4oioJTTjkFq1atgqqykpaIiIiIyhPVgdOtlb8HdWsuS+MSVZMjgsQXX3wRwWAQ3/jGNxCNRvGZz3wGX/rSl/CXf/mXuPnmmwvP27VrF1577TU899xzGBgYwO23347nn38ea9aswR133IGzzjoL999/PzZt2oRLLrmkhn8RERERETmZqA6cc1oCME0gkcpCzxnQXCr8PjfmtPjtmHbdE9WRlsZyRJD4qU99CpdddlnhscvlQnd3N3p6erBp0ybMmTMH9913H7Zt24bOzk4oioJZs2Yhl8vhwIED2LVrF5YsWQIAOP/887FlyxYGiURERER0VCI6cHZ2zMRgNAWfVys5TtaI6hxLpRwRJDY1NQEAEokE/u7v/g533HEHMpkMrrnmGrS3t+PJJ5/Et771LQQCAQSDwTH/Lh6PwzTNwmLg/LEPEwo1QnNo2j8cDtR6CnSMeM3kwuslH14z+fCayYXXyz4XhgOYOrURm17bg30HkpgxrQkXLZmNRadOt/V/px6v2es/342snsOhZBZZ3YBbUzGlyY03dn+AC5e01Xp6RyXb9XJEkAgAAwMD+NKXvoQ/+7M/w5/+6Z/i0KFDmDJlCgDgkksuwUMPPYSLLroIyWSy8G+SySQCgcCY9YfJZLLw744mGh22/4+wARciy4fXTC68XvLhNZMPr5lceL3sd9I0H77wqVPHHLPzHNt9zWQp4Xx7zwFEDx3pHJvJ5vBBLIecEXX0a9jJ77FKwasjurt88MEHuPnmm7Fy5Up87nOfAwDccsst2LlzJwBg69atOO2007Bo0SJ0dXXBMAy8//77MAwD06ZNw8c+9jH89re/BQC88sorWLx4cc3+FiIiIiIiWeRLOAejKRjmkRLO7p6hWk+tRFY3YJgm9JyBbM6Anht9nLWhcyyN5YhM4rp163Do0CE88cQTeOKJJwAA99xzD1avXg23240TTjgBDz30EPx+PxYvXozrrrsOhmHg/vvvBwDcfffd+OpXv4pvfvObmDdv3pj1jUREREREx4N8xi+ayCDk99iS8evaOVDxuNOyiaYJ5HLmkccYfWyalf8NTY5imvV5Wp2c8nXq3Kg8XjO58HrJh9dMPrxmcuH1st/6rb3YvL0fiVQWfp8bFyw8EVee3WZpzOKmLW5NLezHuHzpPEvB3ENPvQ6jTDSgKgq++heTr84TUcJ61xNbcCiZgWGYMAEoAFRVwZQmD/75b8+1NLZITn6PObrclIiIiIjoeLB+ay/Wb+lFYjgLmEBiOIv1W3qxfmuvpXGPlvGzIhz0VTjeMOkxRZWwujUVqqJAc6lwu1RortHH3IPSfo4oNyUiIiKi8kQ1FRFRukjA5u39FY9bySZGYqkKx0cmPSYwujVH8bYSxccnS1QJ65yWANKZHOLDWRimCVVREGjkHpQiMEh0CH5QExER0Xii9oUbX7rI/ebsk0hlyx5PVjg+UeGgD4PR0kDRSsYPOHK9R3+IGEE42GD5PlRUQNs63Y8d73wAl6rAhdHt74ZHdLROZ5BoNwaJDsAPaiIiIipHVEZGZLMSWbZTEMXvc4+Wmo7T5HNbGldExi+vfW6zrddIVEC7d38CwYAXiVQWes6A5lLh97mxd3/C0rhUimsSHUBUjTkRERHJTVRGRtS4Mm2nIMoFC088puMT1T63GWecGkZ8OIP39icQH87gjFPDjgzAKwWuVgPaSCwFn1dDOOjDzOYmhIM++Lya5dctlWIm0QFEfVATERGR3ERlZESNywwlCusON2/vRzKVRZON3U237Y4g0OjBtCkNyOoGtu2OoG1GwHHntn1uM3r3xUvOgdV5inrdUikGiQ7AFzwRERGVI6rEUNS4ojOUeU5fmnPl2W2Wg8LxunYOYCStI57KIpcz4XIpCPjclgNwEee2OKANNHoAwJaAVmTJLY3FclMHEJWSJyIiIrm1z23G8qXz0BLyQVUUtIR8lvfFy48ronRRxHYKAJfmAEDfYBzReBr64f0Rdd1ANJ7GnkFr6/G6dg4gldYRiaUwMJREJJZCKq1bOreirpeo9wOVYibRAYq7SsWSGbSEnFtCQURERLVSZsfzSRJVuihbhlIm2cPB4XgZPWdp3L7BOGLxdOGxrhuIxdPoU5RJjynyetndZIfKY5DoEPkXfDgcQCQSr/V0iIiIyAFElVmKWjsoYjsFQL6lOSLWT7q18gWAVjeSz+oGDMOEYZowTUBRAFVRkLUQfMp2vagUg0QiIiIihxIVzMmW6ZFpLZqowH5OSwAjmRwSw1kYpgFVUeC3YSN5wzSRM45kqU0TyB0OGCdLputF5TFIJCIiInKoSCxVaFaS3xcu4HNbDuZky/SIylCKUNxgpviaWQ3sizeS1xQVpmkiZcNG8qqiwOVSYBgmTAAKAFVVYKHaVKrrReVNOEj85S9/id/85jdwuVw4//zzce6554qcFxEREVHd82gu9MeThcf5ZiXBgNfSuDJmemRZi9Y3GMfQoZFC0KXrBjLZHBQrURdGN5IPBbyj3U0NsxB8Wt1I3q2pUBUFqmvs/DwWy1hluV5U3oSCxK9//evYvn07li1bBsMw8G//9m/43e9+h1tvvVX0/IiIiIjqWIWaPyu1gGDTPJGGUzpyuaLyTQC5nInkSNbSuJFYCg1eDQ1eDW5NLTSysZpVntMSAEyUZD5nWyxjJblNKEh86aWXsGHDBmja6NOvv/56XH311QwSbZRf4BxNZBDye/hBTURERMjoBoIBLxJFN/B+nxsZ3XqnUzbNE6NSt9FM1loXUlElwp0dMzEYHQ1Axx+n+jWhIDEcDuPQoUOYNm0aACCbzSIUCgmdWD0pXuDs1lTHbxBLRERE1REO+mBEU/CNu4F36tpBAjSXilyutFuo5rK2PbmoEmGuH6RyJhQkTps2DZ/+9Kdx0UUXQdM0/PrXv8a0adNw7733AgDWrFkjdJLHu/wmpolUFrmcCZdLgd+GBc5EREQkNxnXDooiYlsJEVrDTegZiEOFUnLciuqUCNu3FyfJbUJB4oUXXogLL7yw8Li9vb3wn60uwqWxm5gqimLLJqZEREQkPxmzPCKCOVHbSoiw7Jw2/HDj2yUlwsvOabM8togSYZnOLVXPhILEz3zmM0f9766++mrbJlSP8guPS49bq10nIiIi+YnqEimiH4KogKO46qo48HJi1VX73GbceOl8aQJ7UXtxktws75NoWuyuRaPrEMux2nqYiIiIqBxR/RBEBRzFVVcAHF91JdP2D5FYaTOc0ePWuqaS3KytoAXLTe0wpyWAUMALTVMBBdA0FaGAl62HiYiISIijBXNWRGIppNI6IrEUBoaSRY+tBRysuhInHPRVOM7mSPXMcpBI1nV2zESDV0M46MNJ0/0IB31o8Gp1uSidiIiIxBOVPfJoKmLxNHTdAMwjGT+PZi2pwKorcSrdb/I+tL5ZLjcl67ihLREREVWTqD33gArBoMXKM274Lo6MzZFIPK5JdAhuaEtERETVImprjYyeQyjgLQnmMtny5aITxQ3fxZJpDSVVxzEHidFoFMFgsLAWccWKFbZPioiIiIjEEVXFlM9Qjg/mrGYome0SS5Y9KKl6jhokHjhwAA888AA+//nP48wzz8Ttt9+OLVu24IQTTsC6devwkY98BFdccUW15kpERERENhFRxSQqQzkWq9jsxH0SqZyjBokPPfQQ2tvb0d7ejp///Od466230NXVhXfeeQePPPIIvve971VrnkRERETkcKIyfgxkxOE+iVTOUYPEd999F//yL/8CAHjllVfwqU99Cn6/HwsXLsT+/furMkEiIiIikoeI9W1dOwcQS6SRGM7CME2oigJ/o5uBjA24TyKVc9QgsXgPxN/85jd4+OGHC49TqfIvKCIiJ8qvt4gmMgj5PVxvQUQkkbf3xnAwkSk8zpkmDiYyeHvvwRrOqvpEfJeJ63RLMt97HDVInDVrFn72s58hlUohlUphyZIlAIAXXngBp5xySlUmSERkVXGZkltTWaZERCSZxHC2wvFM2ePHI1HfZdVZR1p/ZL/3OGqQuGrVKtx///0YGhrC2nxYnG4AACAASURBVLVr4fF4sGbNGvzqV7/Ct7/97WrNkYjIEq63ICKSW84o36ym0vHjUdfOAaTSOhKpLHI5Ey6XAr/PesmtyHWk9dwxVfZ7j6MGiTNnzsR3vvOdMcf+9m//FnfffTdUVRU6MSIiu3C9BRGR3FRFQa7M3txq0dKo413fYBwHDo3AMEyYABQdyGRzY5aHTZbd60jZaEj+e49j3idx6tSpAIBFixbhzTfftH1Ck2UYBh544AHs3r0bHo8HDz/8MObMmVPraU3YzY++VHLsP+/5pCPHlWmuso0r01xlGjcc9OG1t0qbbS356PRJj5knyzkQNSbHFTcmxxU3pmzjyjRXUePObPZhb2S47HErZDoHwykdeu5IoGwCMHImhkfKl+IeC7vn27VzAH37SrdVsSOLJss1E3nvUQ2TTgeaZX7NqaVf/vKXyGQyeOaZZ3DnnXfi0UcfrfWUJqzci/Jox2s5rkxzlW1cmeYq27jlPqSPdnyiZDoHMs1VtnFlmqts48o0V1HjyjRXkeOWCxCPdnwiZDsH8VT5YDBeYb3mRPF7V65zUC2TDhLtSG3badu2bTjvvPMAAAsWLEB3d3eNZ0RERERERCSfo5abvv/++2WPm6bpuExiIpGA3+8vPHa5XNB1HZpW/k8MhRqhaa5qTW/SwuGANOPKNFfZxpVprrKNK9NcRY0r01xlG1emuco2rkxzFTWuTHOVbVyZ5irbuDLNVdS4ouZqp6MGiTfeeCMURSkbEIZCIWGTmgy/349kMll4bBhGxQARAKLRyZcnVFMkUlrP7dRxZZqrbOPKNFfZxpVprqLGlWmuso0r01xlG1emuYoaV6a5yjauTHOVbVyZ5ipqXFFznYxKAetRg8SXXrJW31tNixYtwq9+9StcccUV2LFjB+bPn1/rKREREREREUnnQ9ck9vb24itf+QquuuoqXH311fjKV76C3t7eKkzt2FxyySXweDy4/vrrsWbNGtx77721ntKEVeqcZLVTk4hxZZqrbOPKNFfZxpVprqLG/YfrTj+m4xMl0zkQNa5Mc5VtXJnmCoh5n8l2DkSN2zKtfBfTGdMaJz2mbOdA1LiVum1a6cIp23eOTO/dalHMoywufOutt3DzzTfjs5/9LM4880xks1m8+eab+J//+R9873vfw5/8yZ9Uc662clKat1g4HHDs3Kg8XjO51Ov1WvdCNwajpXs2tYR8uPWq9hrMaOLq9ZrJrF6vmazvMxmu17oXutG3L454Kgs9Z0BzqQj43JgzI+DocyuKndds/J6GecuXzpv0dhUyvhe6e4bQtXMAkdgIwsEGdHbMtG1PRye/xyZVbrp27VqsXbsW55xzTuHYJZdcgnPPPRff+MY38N3vftfeWRIRkRCyb+pLJAO+z8Tp7JiJwWgKDV6t5LgTHQk4UggHfbYGHHbLz8vOAEnG90L73GbHXqNaOGqQGIlExgSIeZ2dnVi9erWwSRERkb3CQV/ZX3XDwYYazIbo+CTb+ywfyEQTGYT8nroLZEQZn5kbjKYKj504X8D+AEm29wIgV2BfDUcNEoeHK3cAzeVytk+GiIjE6OyYWbacyKm/whPJSKb3WXEg49bUugxkROnaOVDxuAzzt4NM7wVAzsBetKM2rlmwYAG+//3vlxz/9re/jTPOOEPUnIiIyGbtc5uxfOk8tIR8UBUFLSGfpfUmRFRKpvfZ0QIZskbGUku7yfReAPh+KOeomcR77rkHf/7nf46XXnoJHR0dyOVy2L59O0ZGRvDUU09Va45ERGQDWX6FJ5KZLO8zBjLiyFhqKYIs7wWA74dyjhokNjc34yc/+Ql+9rOf4Xe/+x0URcENN9yAyy+/HB6Pp1pzJCIiB+M6DiL5hIO+QrfQXM6Ey6UUuoU6lSyfNbKVWtLY98P47rn16qhB4vvvvw8AOOuss3DWWWcVjn/wwQcAgFmzZgmcGhEROR3XcRDJqXW6HzveGb2fUxQFum4gGk/jXIcGMjJ91sjUZIdGFb8fADj+/VANRw0Sb7zxRiiKgnJbKSqKgk2bNgmbWL2RqcMYEVEeGzQQyWnv/gSCAS8ShzOJmqbC73Nj7/6E5bFFZPxk+6wRVWrJ+0Uxit8P+UyiXe8HWR01SHzppZeqNY+6JmOHMSIigOs4iGQViaWgjDumwPp7V1TGj581vF8UKRJLwefV4Bu3D2c9vb7GO2qQmNff348f/vCHOHjw4Jis4po1a4RNrJ7I9usYEVEeGzQQycmjudAfTwIYW24aDHgtjSvqnoafNbxfFImvr1ITChLvuOMOLF68GIsXL4aijP/diazir2NEJCs2aCCSVelSotHDFY5PkKh7Gtk+a0SU3PJ+URzZXl/VMKEgUdd13H333aLnUrf46wURyYoNGkg0WTpayiajG2XXJGZ0a0GiqHsamT5rRJXc8n5RHJleX9UyoSDxjDPOwEsvvYTOzk5ufSEAf70gIpnJtBcWyUWmjpayCQd9MKKj67Dcmoqsbhw+bi3gEHlPI8tnjaiyUN4viiXL66taJhQk/vznP8fTTz9dcvytt96yfUL1qPjXi1gyg5YQfyklIiLiGixxRAUczMiIKwvl/SJV04SCxBdeeAEbNmzAoUOHRM+nbuV/vQiHA4hE4rWeDhERUc1xDZY4IgOOes/IVKMs1OLS0apgqbjcJhQkrlixAqeeeipmzZolej5EREREALgGSzRRP1CLCg7Wb+3F5u39SKSy8PvcuGDhibjy7DbL49pNVJZWpi0wWCouvwkFiQCwevVqkfMgIiIiGoNrsOQjKjhYv7UX67f0Fh4nhrOFx04LFNvnNqN3X7wkoLUaHMlUfi3TXKk8dSJPuvjii/Hcc8/hvffew/vvv1/4PyIiIiJR2uc2Y/nSeWgJ+aAqClpCPixfOo83mQ52tODAis3b+4/peC119wxh2+4IAo0ezGxuQqDRg227I+juGbI0rkzl1zLNlcqbUCZxeHgYq1evRigUKhxTFAWbNm0SNjEiIiIiUevbuF5KDFHBQSKVLXs8WeF4LYnKooksv7b7/cBScflNKEj81a9+ha1bt6KhgReWiIiI5Mb1UuKICg78PjcSw6UBYZPPbWlcEUQFytVY6wjY835gqbj8JlRueuKJJ+LgwYOi50JEREQknKiSSKocBFgNDi5YeOIxHa+lcNBX4bi1QLl9bjPOODWM+HAG7+1PID6cwRmnhoWudZwslorLb0KZxGw2i2XLluGUU06B233kF5v/+q//EjYxIiIiIhG4XkocUfsk5pvTbN7ej2Qqi6Y67W6aX+s4bUoDsrqBbbsjaJsRsHR+Re7ryKBQXhMKEm+99VbR8yAiIiKqCq6XEktUcHDl2W2ODArHK+5uWhzQOrW7Kd8PVM6EgsQlS5aIngcRERFRVXC9FInU3TOELTsHMJLJwQQwkslhy84Bx2b8+H6gcia8TyIRERHR8UBUSSSJJUtH2g2v9iEaTxce67qBaDyNDVv7HJnx4/uBymGQSERERHWH66XkIlNH2r2RRPnj+8sfnyiRGT++H2g8BolEREREdSifmYsmMgj5PY7OHolajyeT4oxfLJlBS8i52VRAnswvlccgkYiIiKjOFGfm3Jrq6MwcIFdH2tZwE3oG4mWPW5XP+IXDAUQipf8bTiFT5pfKm9A+iURERER0/JBtr0hRew+KsOycNgQDXmiaCiiApqkIBrxYdk5bradWNbK9vqgUg0QiIiKiOiNTZg6ovO7OiR042+c248ZL56N97jSceIIf7XOnHX5cPxk02V5fVIrlpkRERER1Rra98WTrwFnvjWBke31RKQaJRERERHVGxr3xZAq86r1pS2fHTPxw49tIpLLQcwY0lwq/z+3o1xeNVfMgMR6PY+XKlUgkEshms7jnnnuwcOFCbNy4Ef/0T/+EmTNHX0y33347Fi9ejAceeAC7d++Gx+PBww8/jDlz5mDHjh145JFH4HK50NnZidtuu63GfxURERGRc4nslFnvARKbtoxSPuQxOVvNg8Tvfe97+MQnPoEvfOEL+OMf/4g777wTP/3pT7Fr1y6sXLkSl112WeG5GzduRCaTwTPPPIMdO3bg0UcfxZNPPolVq1bhsccew0knnYQVK1Zg165dOO2002r4VxERERHZQ1TQJaJTpsgASZbgk9t1jP6tDV4NDV6t5Hi9nAPZ1TxI/MIXvgCPxwMAyOVy8Hq9AIBdu3bhrbfewlNPPYWOjg7cdddd2LZtG8477zwAwIIFC9Dd3Y1EIoFMJoPZs2cDADo7O7F161YGiURERCQ92bJSogIkmc4Dm7bwHBwPqhokPvfcc3jqqafGHFu9ejU6OjoQiUSwcuVK3HfffQCAc889FxdffDFaW1uxatUq/OhHP0IikYDf7y/8W5fLVXKsqakJ77333ofOJRRqhKa5bPrL7BUOB2o9BTpGvGZy4fWSD6+ZfOr1mr25ez9++doe7BtKYkZzEy5eMhuLTp0+6fFe//luuLXSZvRv7P4AFy5pszBT++cKANFEpux8Y8mMpdeEyPNgt9aWKRj4IFFyfNYJflvfF05+j1XrHMhEtr+7qkHiNddcg2uuuabk+O7du/EP//AP+Md//EcsWbIEALB8+XJMmTIFAHDRRRfhF7/4BQKBAJLJZOHfGYYBv98/5lgymSz8u6OJRoet/jlCOH1zVCrFayYXXi/58JrJp16v2fhs1559h/CfL3bj4NJ5k8527R08BMMsPf7eYNzSOS6eq1tTbZkrAIT8nrJdLVtCPkvz3Tt4CMkRvaQRSi5n7TyIcOapJ+D5fYdKji8+9QTb5ur091g1zoFMnHy9KgWvNd8n8d1338Xf//3fY+3atVi6dCkAwDRNfPrTn8a+ffsAoFA+umjRIrzyyisAgB07dmD+/Pnw+/1wu93Ys2cPTNNEV1cXFi9eXLO/h4iIiOqTiA3ERW0iL2qz886OmRhJ64jEUhgYSiISS2EkrVvuaunRVMTiaei6AZiArhuIxdPwaM5rh9I+txnLl85DS8gHVVHQEvJhucXgWzY8B/Kr+ZrEtWvXIpPJ4JFHHgEA+P1+PPnkk3j44Ydx2223oaGhASeffDKuvfZauFwubNmyBddffz1M08Tq1asBAF/72tdw1113IZfLobOzE6effnot/yQiIiKqQyLWYYnaqkLkmrHxic8yidBJqBAMKs4LEgG5tusQhedAbjUPEp988smyxzs7O9HZ2Vly/MEHHyw5tmDBAjz77LO2z42IiIhookRsIN4+txm9++LYvL0fyVQWTT43Llh4ouWbb1GbnXftHIDPq8Fnc1fLjJ5DKOBFvKjcNOBzI5M1LM1Xlo6povE80Hg1DxKJiKoh/wUYTWQQ8nv4BUhEthOR9evuGcK23REEGj0INI52g9+2O4K2GQFLn2GyZSjzQe34LRWsBLUydUwVqbtnaMzG94PRFHr3xXHjpfMtd6Rl4Cmvmq9JJCISLX8jMBhNwTTNwo1Ad89QradGRMcREeuwRK0dHDNX1b41Y6LWUFYKXq0EtaLOrWw2vNpbdr3nhld7Jz1m8feuYYLfuxJiJpGIjnvc2JiIqsXudVgi1w7m52pn50VRGcr8OR3NTI0gHGywnJmScS8/EVUxeyPJYzo+EfzelR+DRCI67sl4I0BEcrK7xE7U2kFRRARzxWPbGWDIdm7Hb1vi5PJYfu/Kj0EiER33ZLsRICI5iVjjJiozJ5IsXS1lO7eisnOtYT96Bkr3NGyd7p/0mPzelR/XJBLRcU/EWhYiovFErHGTcb+57p4hrHuhGw899TrWvdDt2HVosp1bUdm5ZefMQWODhpxhIpszkDNMNDZoWHb2nEmPye9d+TGTSETHveLyp1gyg5YQu6wRkf3El9jZs+OgSLJ1DJUl6wmIzc553S5kPEZhexGv22VpPJFlx1QdDBKJqC6IaNBARFRMxE28bEGXyIYl67f2YvP2fiRSWfgP7xd55dltlsYURcT2D6LKY0VdM5kCcCrFIJGIiIjIBiJu4mXrEikqm7p+ay/Wb+ktPE4MZwuPnRYodvcM4T83vIX4cBaGaWLPYAJvvxfDzcs+ajnoAuyviukbjCMaTxce67qBaDwNRVEsjUtyY5BIREREZANu0yCuJHLz9n4YpgnDMGECUACoqoLN2/sdFyQ++9K7iCUyhcc500QskcGzL72L9lusBXQiqmKyulH2eEbP2TI+yYlBIhEREZFN6n2bBlElkYeSGeRyR9ZkmgByORPxZNbSuCK8/0H5/QUrHT8WIvZJdGvl+1i6NWvrEkWU3Iocl8ZikEhERETkULJt0yCqYYmqKNDLNO5xYkWkUaG/UKXjEyVqn8Q5LQGYJpBIZQuNa/w+N+a0TH4LDFFraWVboyszboFBRERE5FCybdMwln3dWN3uCtkui104RVArRK6qai2iFbHFCjD6g4PPqyEc9GFmcxPCQR98Xk3YWlorRI1LpZhJJCIiInIwmbpEdvcM4emNbyN+OCs1GE2hb18cn790vqW/QUWFwMuBmcRZJzRib6S0tHRWc6OlcSOxFFJpHYlUFrmcCZdLgd/ntrw+Vaa1tLKt0ZUZg0QiIiIissWGV/vKdsrcsLXPUtCRzRllw8RKTVdq6dpPfmRMd1NVURBodOPaT37E0rgeTUX/4XOrKAp03UAsnkbI77E8Z1nW0sq2RldmDBKJHISLsYmISGZ7I4nyx/eXPz5RLlWBqirIFS3sc6kKXA5MJbbPbcbNyz4qYCP5Cn+rAxdmilpLK9saXZkxSCRyCC7GJiIiKi8U8KA/MjwmTDIME6GA9SyaCCJKhDN6Do0N2uEMpVHIUGayzsumimpgJGpcKsUgkcghZNswmYiIaLzWcBN6Bkr372sNN1kat6nBA0UdhlEUD6kq0ORzZpAogkdTER/OFrKpOdNEfDiLlpCvxjMrT9RaWpnW6MqM3U2JHIKLsYmISHbLzmlDMOCFpqmAAmiaimDAi2XntFkaN5ZMQ1UUqMpodaWqjHYRPVi0af3xbuhQeky5LQDkDBNDh9IV/gXR5DGTSOQQXIxNRESya5/bjM6Omdi8vR+JlIEGj8uWcsCsPlpeqbrGrr/L6DlL48qkuCHQRI4fr9i/oToYJBI5BBdjExGR7Lp7hrBtdwSBRg8CjaOloNt2R9A2I2DpRt6tVdgnUXPePomAmEDGMMvvO1np+PGI/Ruqh+WmRA4h94bJRERE4jY7n9MSgK9BQ84wkc0ZyBkmfA0a5rT4LY0rQj6QGYymYJhHApnuniFL47oqdDGtdPx4JOr1RaWYSSRyEC7GHsVSEiIiOYlaX9863Y8d73wwuu3F4R6nqREdrdOdFySKakTnb3IjFi9dg+lvst68R5bvXfZvqB4GiQ6Rf3NGExmE/B7HvjmJRGMpCRGRvEStr9+7P1G0/cORDeqt7r8ogqhAZn5rELvfiyFRdA78jW7Mb51qaVyZvnfZv6F6WG7qAMVlCaZp2laWQCQjlpIQEcmr0jp6q+vr+wbjSKSyMA+vvzNNE4lUFnsGnRckhoPlt6SwGsh0dsyE1+2C1+OCRxv9/163y/K5lel7t7NjJkbSOiKxFAaGkojEUhhJ6+zfIAAziQ7A/fGIjmApCRGRvNrnNqN3Xxybt/cjmcqiyefGBQtPtHw/M5zSkcsdadBiAsjlTCRHshZnbD+RjeiUcf/BjtWIor53RZWwjm/TUz9te6qLQaID8KaY6AiWkpCMZFnPQySaqO6mGT1XNhjIZJ23BUb+7xz9TBhBONhgy2dC184BNHg1NHg1uDUVWd0oHLcytojvXVElrF07B+DzavB5tZLj/My1F4NEB+BNMdER3AqEZCPTeh6iYiL6IbA6apSIRnSikgoivndFvQ6YWKkerkl0AFH1+0Qy4lYgJBuZ1vMQ5YnqhyDqJt5TYT9Ej9uZ+ySKIGqto4jvXVGvA1HngEoxk+gAxWUJsWQGLSGWKlF941YgJBP+sk0yEpXpEVUdVWndWR3tIy+00sbu791w0IfefaPNhvScAc2lwu9zo21GwNK4nR0z8cONb5eMy8SK/RgkOkT+zRkOBxCJxGs9HSIimiAuGSAZyVS6CAAjGf2Yjh+PZEoq5Pe1zNN1A7F4Gq12Nu+p8JjswSCRiIjIAq6jJRmJ+nFDVNOW4s6mEzl+vJIlqbB3fwKhgBfxooxfwGd9X8vi5j3jjzsxWJZZzYNE0zRx/vnno62tDQCwYMEC3HnnnXjppZfwrW99C5qmYfny5bj22msxMjKClStXYmhoCE1NTfj617+OadOmlX0uERFRNYi6KSYSSabSRQBQlPKlpQrTSLawu0NzJJYqG8xZzVSzvL96ah4k7tmzB6eddhrWrVtXOJbNZrFmzRr8+Mc/hs/nww033IALL7wQ69evx/z583H77bdjw4YNeOKJJ3D33XeXfW44HK7hX0VERPWE62hJNjKVLgKA1+1CKlO63YXXUz+Na0QR0aFZVKaa5f3VU/MgcdeuXRgcHMRNN92EhoYG3HvvvchkMpg9ezamTp0KADjjjDPwxhtvYNu2bfjiF78IADj//PPxxBNP4A9/+EPZ515++eU1+5smQ0QbaiKiYtzLj4iKyVK6CABT/B6kYykYxpFjqgpMbfLWblLHCRFNjERlqlneXz1VDRKfe+45PPXUU2OO3X///VixYgUuv/xyvPHGG1i5ciXuvfdeBAJHuh81NTUhkUggkUgUjjc1NSEej485VvzcDxMKNUKr0E652t7cvR8vbuktPD4QT+PFLb2YOrURi06dXruJ0YSFw9a6dVF11eP1Kv6ccblU6T5n6vGayY7XTC5Ov17zZ0+DS43hUDKDbM6A26ViSpMHH2kNOn7uotj1d0cTGbi10l3xYsnMpP83LgwHMHVqIza9tgf7DiQxY1oTLloy2/L3jahxq0G212lVg8RrrrkG11xzzZhjqVQKLtdosLZ48WIMDg7C7/cjmUwWnpNMJhEIBMYcTyaTmDJlSsXnfphodNiOP8kWG379B2T10Z/G3Jpa+M8bfv0HnDSt/H4w5Bwy/AJLR9Tr9Sr+nBl/3OmfM/V6zWTGayYXu6+XiKqFM089AXv2HULz1LFlhYtPPaGuXmsiKs9Cfk/ZEs6WkM/SuT14cBgj6Syy2RxG0lkcPDhsy7U6aZoPX/jUqWOOOf014OTPxErBa+nPBlX2+OOPF7KLv//97zFr1iycfPLJ6OvrQywWQyaTwRtvvIGFCxdi0aJFePnllwEAr7zyCs4444yKz5UJF+ESkWj8nCGiasivbxuMpmCYR9a3dfcMWRpXxIbvsik+t6Zp2nZuOztm4mAijb37E9gzGMfe/QkcTKQtlXCKeh1Q9dR8TeKKFSuwcuVKvPzyy3C5XFizZg3cbjfuuece3HLLLTBNE8uXL0dLSwtuuOEG3H333bjhhhvgdruxdu3ais+VCRfhEpFo/JwhomoQsb6tlPO3vRCRTRV1bnv3xZEYzsI0TcAETJhIDGfRuy8+6XGr8zogkWoeJE6dOhXf/va3S45/8pOfxCc/+ckxx3w+H/793/99Qs+VCRfhEpFo/JwhomoQVbUgogOnKKLmKurcbt7eD1VVoI7bln7z9n5ceXbbpMZk9Yr8al5uSuNKKNT6LKEgIrFYqkVE1RAOll/jbLVq4WiZKacRNVdR5zaRypY9nqxwfCJEzZWqp+aZRBolUxtqIpIT9/IjItFEVS2IzFDaXRYqaq6izq3f50ZiuDQgbPK5Jz0mq1fkxyCRiIiIiGyRD7BGA68RhIMNtgReItZViyoLFbUGvPjcxpIZtITsCWovWHgi1hdtxVZ8fLJEvQ6oehgkEhEREZEA9jWYEZGZEtVcRWQWTUTl2ZVnt2HwwDBef2t/YQ/KMz86fdLrEcfPleTEIJGIiIiIbCEqOyciMyWqLFS2LFp3zxD2RpKYeUJT4djeSBLdPUOOnTOJxyCRiIiIiGwh0xYYIrcGkimLxu0qqBx2NyUiIiIiW4jeAsPOzdkrlX/WW3MVbldB5TBIJCIiIiJbyLQFBrcGGsXtKqgclps6RL4FczSRQcjvcXTtOhEREclPxL2HyC0wRtI64qks9JwBzaUi4HPbsn5Qpvstma4ZyY1BogMUL/J2a6pti7yJiIiIyhF17yGqaYtHc6E/niw81nUD0XgawYDX0rgyke2akdwYJDoAFwwTERFRNYm89xCTnavQrMa0b5sNO+UzfpFYCuGgPfsZynfNSGYMEh2AC4aJiIiommS798joBoIBLxJF5aZ+nxsZ3XlBoqhtQIpLbnM5Ey6XYkvJLVE5DBIdIBz0oXdfHImiN73f50bbjP/f3t0HR1XdfQD/3t27Gza7GxJgE9BAEmihtoHyVls0vEhBLNBCh+KU4kOfQos6osUOb1osOkRextoXFay21nGsHVFoCwVfW0EEMjwFCU5ChdYmaCIkS5rI7maTfbvPH8suSXaDhrtn957k+/lH97hz52zOHvf+7u+c33FmumtERETUC4k8/kEEV64NkWY/bFlql3bj9VdUxq/jkltFUQy/5HZvRS0OnKiH1x+Ew2bBtHHXYu6k4kx3iz4jVjc1gMJ8B1o87QiFIgCi6+xbPO0ozHdkuGdERETUG8l2/INM/Y1l/Nwtfpxr8nV4rTfjJ8+S270Vtdh7uBbe1iCgAd7WIPYersXeitoM94w+KwaJBlDX6EWeMwuqagIUQFVNyHNmoa7Rm+muERERUS/U6fgHk/GPfygtGYgJo1zwtAZwrskHT2sAE0a5DNlfq2pGc+zhv3a5yI7Vou+2O7bkVlWj11FVE3KdWYZccnvgRH2P2sl4uNzUANwtfvTLUtEvS4VFNSF4KaPINeZEREQkSqxYicvlhNvtyXR3rqiqpgnHT7vhzLbCmW0FABw/7UbxYKcBA0UxGb+OS2473i8accmt1x9M2u7rpp2Mh0GiAci2L4CIiIioO7JVAWu26gAAGvdJREFU9kw1UUV2ZDrP0GGzRJeadmG3WTLQG7oaDBINQKZJT0RERNSddFT2jAVeRq3sKarITsfzDFt8ARTkpSYAF2HauGux93Bt0naSA4NEA5Bp0hMRERF1Jx2VPQEYurKnyIf/siwRjlUxPXCiHj5/EHZWN5UOg0SDkGXSExEREXVH3PmL8lT27Pjw393SBlduvz758H/upGIGhRJjkEhEREREKSGqzoKofX6ixB7+E8mKQSIRERERpYSopZai9vmJIqJ4T8frNnsDyHNY+2SGktKDQSIRERERpURpyUDUnvfgwIl6eP1BOC7tRdMbyMhU5K+qpgl/eONMPOvZ0OxH7XkPbrt5pK6/Q8eiQBbVlLKiQKLsrahN+B5w+ak89J3qSURERER0ScfzDIcMtMOZbcXx025U1TTpum5pyUAsmDocBXk2mBQFBXk2LJg63JDB0b4jtWjxtCMUigBatMhOi6cd+47U6rrulYoCGc3eilrsPVwbPQZDA7ytQew9XIu9FbUZ7hl9VswkEhEREVFKiDzPUJZ9fnVuX4/aPytxRYFS78CJ+m7bjZpNFLVEWFYMEomIiIj6IBH722QKZGQjqiiQCF5/MGm7r5v2TBN1vqfMuNyUiIiIqI+J3RQ3NPuhaVr8pljvslBXrq2bduMFMqIUuhzJ2/OTt39W3e2/TMW+zKqaJvxmdxU2PvcP/GZ3le7vgcNmSdpu76Y902RaypsuDBKJiIiI+hhRN8UiAxlZzLmhCHnOLKiqCVAAVTUhz5mFOZOKdF23075MU+r2ZXZ8YBDRkJIHBtPGXduj9p5IdUALMAOeDJebEhEREfUxom6KeZB89G+w+OaRQv4GsX2ZLpcTbrcnBb0Vs480tu/wwIl6+PxB2FNU3VTUslCZlvKmC4NEIiIioj7GlWtD7XkPvP4gwmENZrMCh82C4sFO3deWpcCMSDL9DdwtfvjbQ/EjO1SzCQ6bRfcDg7mTilNepEZUYSSZjlhJFy43JSIiIupjCvMdl49pwOVjGvTumyP5WFVT0iM7rKqS6a4lEJkBl+WIlXRhJpGIiIioj6lr9CLPmQWPP4hwRINqNsFps6Cu0ZvprtEViKhIC3QTDCrGCxJFLguVKfubDhkPEp9++mm88847AICLFy/iwoULOHz4MJ599lns3LkTAwYMAAA89NBDuOaaa7B69Wo0NTXBbrdj69atGDBgAN566y1s27YNqqpiwYIFuPXWWzP5kYiIiIgMzd3iR78sFf2yVFhUE4KXMop9uVCH0XXcj2dRTSnbjxcIheMPDGLLTZ02CwLBSEr6nUpcFpo+GQ8Sly9fjuXLlwMAbr/9dqxatQoAUF1dja1bt6K0tDT+3meffRYjR47E3XffjX379mH79u1Yu3YtNm/ejJ07d8Jms2HRokW46aab4HK5MvJ5iIiIiIyOhTrkI2o/Xuy70C9L7dJuvO8CCyOlT8aDxJg33ngDOTk5mDx5MoBokPj000/D7XZj2rRpuP3223H8+HH88Ic/BABMmTIF27dvxwcffIBhw4ahf//+AIAJEybg2LFj+MY3vpGxz0JERER9U2w5oLvFD1euzbA3sGVjhuCFN85El5teKlzjtFmYkTEwUfvxZMvOcVloeqQ1SHz55Zfx3HPPdWrbtGkTxowZg6eeegq/+MUv4u1z5szB9773PTgcDqxYsQL79++H1+uF0xmtumW32+HxeDq1xdq93k9fT5+Xlw1VNafok6WWy6W/shilF8dMLhwv+XDM5NMXx+zd043Yc7gWAGA2m/BfTzv2HK5F//7ZGD8qP7Od66L/f/0IhiMIBMMIRzSYIwqCVjP698/uk2Mng8KCHJy7cPke16JG609eM8iha8xucjnRv382/v5/H+L8f30YPMCOr18/zHDfWdnJNq/SGiQuXLgQCxcuTGj/97//jZycHBQVRQ8Z1TQN3//+9+PB39SpU3Hq1Ck4HA74fD4AgM/nQ05OTqe2WHvHoLE7zc2tqfhIKZfKc28oPThmcuF4yYdjJp++Omb73vkgvreva/vQAbYM9Kh7f3z1FC76AohENABAJKLhoi+AP756ynB9FUmWzC8AfGXUIOw6fxEAOu0jnThqkO75NnSADf97y6hObX1xDoti5P8ndhe8GmK56ZEjRzBlypT4a6/Xi7lz5+KVV15BdnY2jh49igULFsBms+Htt9/GmDFjcPDgQUyYMAEjRozA2bNn0dLSguzsbBw7dgzLli3L4KchIiKivkjUckARgUxtgxehsBZ/rQGIhDXUNvSd6qaiDmYXpeN+vBZfAAV5xg5qSW6GCBJrampw4403xl87nU7ce++9WLJkCaxWKyZNmoSpU6fi+uuvx9q1a7Fo0SJYLBY8+uijsFgsWLduHZYtWwZN07BgwQIUFBRk8NMQERFRXySiGIyoQCZZxvNK7b2RqEIwIsX24xk5M0W9gyGCxA0bNiS0zZ8/H/Pnz+/UZrPZ8NhjjyW8d/r06Zg+fbqw/hERERF9GhEFQGQMZGQhKvMLyLWMlSgZQwSJRERERMnIdLMtojy/qEDGYlbQHtGStvcVoo4BkW0ZKyDXPKP0YJBIREREhiTjzXaqy/OLCmSKB+fgg/pPENE0aAAUACZFQfGQHF3XlYmoox9EZn9jwVyzN4A8hzUlwZxs84wBbXowSCQiIiJD4lJLcYHMnBuK8Pt9/4SnNQhN06AoChzZFsyZVKTruoC4m/hUX1fUwewiCxh1PNuy3qzg7HkPFt88UlefZZpnsgW0MmOQSERERIYkcs+YLEQFMgCQZTEjYI1Ez0k0Kciy6D8/WtRNfMcAKRSOoKHZn5IAScTB7KKyv/uOnEWzpx0AoCgKQqEImj3t2Fdx1pBLmkWQKaCVHYNEIiIiMiRRN9uyERHIHHrvHPplqeiXpXY6c0/vzbaom/iOARKAlAVIIpSNGdIpoFXNJjhtFt3Z3zq3FxFNQyTSYYmwSUFdo75jS2SaZzIFtLIzZboDRERERMl0d1Ot92abxN1si7punTt5IKQ3QBKla0mgxBJBPReKaAiHNWiXLqZpQDisIZykAFFPyDTPXLm2btqNF9DKjplEIiIiMiSRSy1lImKPn6jskUxZKVFEZVOtqgmBQDih3aLqy/mImmcivrdlY4bgD2+cgbdDltaRgiwtJWKQSL0eq2AREclLxFJLmYja4yeqII6o6xa67Kg5l3h4fKHLruu6Ipxt8KCly9LYFk87zir6jhfJ7qfC5w8ioiGemjQpQHY/i67rAqmfZyILzHT9K/adQ1vSi0Ei9WqsgkVERDITlZUqLRmIo6ca8I9/NiIYjsBiNuEr1+Xr/m0UlZWac0Nx0gzSnBuKdV1XhNj+zsT2xCxgT+TarWj6pA3osicx164/SEz1A3VR39uOe2lTeV1KxCCRejVWwSIiIpmJ2uO3t6IW//hnIwDAqpqhaRr+8c9GFAzIxtxJxbquLSL7W1oyELfdPFKKpccW1ZS0wIxV1Vs9Vkm+2VFnhlLEA3XZ9rxSIgaJ1KvxfyZERCQzV64NZ897EiplFg126rrugRP13bbrDRJFkWXpca49K5rx66K/w6rrui2+dmgAYnVqYvFhizeg67oiHqhzz6v8WN2UejVWwSIiIpkV5jvQ9Ekb2tpDCAYjaGsPoemTNhTmO3Rd1+sPJm33ddNOPaHBpChQzSZYzCaoZhNMioJ4WdKr1OoPIRLRoCAaHCoAIhENrW36xkzEA3VRFVPLxgyBvz0Ed4sf55p8cLf44W8PsXCNAMwkUq8magM9ERFROlT/pykaDcTWLSL6z+r/NOnK+DlsFnhbE4MLu814+9tkEwhFkOvMStg/GQjpCxKD4e72OiZv/6xcuTbUnvck9LdYR7ZaZGViFq5JDwaJ1KuxfLpYff1GgIhItDq3DyZFgcmsJLTrMW3ctdh7uDZpux4sGBcNuiLNfti6FFfRu4rJbFJgNiuX9zoq0b2OZpO+MKkw34HKf12Iv45VYy3U+UBdxPJgFq5JHwaJ1OvJsodBNrwRICKSVywLeeBEPVrbQrDbLJg27lrd+xFZME7sMSAffHwxabsedY1e5DmzEva91jV6dV1XhNjy0q5ZT9aaSD0GiQYRy8g0ewPIc1iZkSHD440AEVGiVK+wKHQ5UHMuSWCgc08iEA0U504qhsvlhNudeAbh1WDBuOiD0trzHhw4UQ+vPwjHpQBc72/jl4YPxAf1Xb4LWrRdD3eLP2l2zohjZlVN+OhiWzybGgpFEAiGkaezKBAlYuEaA4hlZBqa/dA0LZ6RqappynTXiLrFGwEios46/p5HNKTk93zODUXIc2ZBVU2AAqiqCXnOLMyZVJTCnqcOC8ZFvwfHT7vhzLZiyEA7nNlWHD/t1n1fV9fohSPbAuXSkReKosCRrT/jJ9OY+dpCCIe1aA0gLVoLKBzW4GsLZbprvQ6DRAO4UkaGyKhk+lEhIkoHEb/npSUDsfjmkSgtGYBrBzlQWjLg0mtjrtgQVdVSJofeO4e2LhU429pDuu/rzjZ40NoWgvnSmYtmk4LWthA+bNAXJMo0Zs2edpjNSvRoSCW6L9NsVtDsac9013odLjc1AGZkSEasHEtE1Jmo33OZ9tazYFw0mOsYtIRCETR72uMZwKvVXRXTQCis67qyjVmyQk6UegwSDYAHg5KMZPtRISISTdTvuWyVpGUKakUIhiKIRDREtOiySEWJBjZ6gzmLmnwBoEU167ouIM+YxYr3xCu8IlrhVW/xHkrEINEAmJEhWcnyo0JElA4ifs9ZSVo+EU1DOHL5TERNA8Kahoi+YxJRVOCEpgFefxDhsAZVjVb2LCrQX8RIBBEPNzoV74lFiSko3kOJGCQaQMeMTIsvgII84z8lJCIios5ErLBgJWn5mJQu5xkimu3SeZwhysYMQcOl8xctqim+/NSISQVRDzfqGr0Y0L9fwhEYRjyuQ3YMEg0ilpFJZRlqIiIiSq9Ur7Bg3QL5dLcs1KpzWahMSQVRDzfcLdEg2SbBcR2yY5BIREREZFCsWyCfXHsWmj5JDFr6p+AsP1mSCqIebnA+pA+DxF5Ots3uREREMkv17y7rFshIi+6Xu/SvsX1z0cP9+gZRwRznQ/owSOzFuNmdiIgofUT87rKStFgiHqa3+AKXA8PYPkQFaPEF9XZXGqKCudKSgag978GBE/Xw+YOw2yyYNu5azgcBGCT2YtzsTkRElD6xQ9Q9HYpqOG0W3b+7rCQdleqATtTD9GAokvQsv6DOIzBkIurhRlVNE46fdsOZbYUzO7p89/hpN4oHOzlHUoxBYi/Gze5ERETpI+oQdRIT0Il6mC6qcI1sRDzcYAIkfZJ/i6lXcOXaumnn5l4iIqJUix2iHgpHEAxFEApHX+s9RJ2uHBxcLVEP04sKnMhzZkFVTYACqKoJec4sDDPoeYYyYQIkfZhJ7MW4uZeIiCh9RB2iLkps+WazN4A8h9XQex1FBAcii6s0NPvRr8sxDbz/0o/VTdOHmcRerLRkIBZMHY6CPBtMioKCPBsWTB1u2B8AIiIimcUOUVcUAAqgKIDZrP8QdRFiyzcbmv3QNC2+fLOqpinTXUtKxOqo7oK2VBRXmTDKBU9rAOebfPC0BjBhlIv3XykgaswoETOJvRw3uxMREaWHRTUlLVhixL1osu3tKhszBH944wy8HYoCOWwWXcEBi6vIh9V+0ycjQeKbb76J1157DY8++igAoLKyEg8//DDMZjPKysqwYsUKRCIRPPjggzh9+jSsVivKy8tRVFTUo/cSERERpUtRgRPtgTA8rUFENA0mRYEz22LIvWgy7u3qmpBNRYKWxVVkZtB13L1E2oPE8vJyHDp0CNddd128bcOGDXj88ccxdOhQLF++HNXV1aivr0cgEMCOHTtQWVmJLVu24Mknn+zRe4mIiIjSpTDfgcp/XYDZpMB8KYRpbQuhMN94QaJse7sOvXcO/bLUhH1+Rgy8ZAzAZcEzwNMn7UHi+PHjMWPGDOzYsQMA4PV6EQgEMGzYMABAWVkZKioq4Ha7MXnyZADA2LFjUVVV1aP3EhEREaVTXaMXuc6shCWRdY3eTHctgcjidiIOqJcp8JItAJcJs7TpIyxIfPnll/Hcc891atu0aRNmz56No0ePxtu8Xi8cjstP2Ox2Oz766KOEdrPZ3KP3hkIhqGr3H8/lcur6fCIZuW+UHMdMLhwv+XDM5NMXx6zZG0CO3Yocu7VTe4svYLi/x00uJ9yeAF47UouLrQHkZFtxyw3FuOn6Yl3Xffd0I/YcrgUAmM0m/NfTjj2Ha9G/fzbGj8q/6usWFuTg3IXEYPuaQQ7D/W3nTB6B5185lbQ9lX012udOh2ZvIOk5lEacY10ZvX9dCQsSFy5ciIULF37q+xwOB3w+X/y1z+dDTk4O2traOrVHIpEevfdKASIRERFRqv1i5dRMd6FHbv36SNz69ZEpveb4Ufm6gsHurPmfiSm/piii/gYk3xyTWcaPwHA4HLBYLPjwww+haRoOHTqEiRMnYvz48Th48CCAaGGbkSNH9ui9RERERERE1HOGSLc99NBDWLVqFcLhMMrKyvDlL38Zo0ePxuHDh/Hd734XmqZh06ZNPX4vERERERER9YyiaRrrxxIREREREREAAyw3JSIiIiIiIuNgkEhERERERERxhtiTSNGKrA8++CBOnz4Nq9WK8vJyFBUVZbpbdAXz58+H0xktZ1xYWIjNmzdnuEfUnZMnT+LnP/85nn/+eZw9exbr1q2Doij4/Oc/jw0bNsBk4vMyI+k4XtXV1bjjjjtQXFwMAFi0aBFmz56d2Q5SXDAYxP3334/6+noEAgHceeed+NznPsc5ZmDJxmzw4MGcZwYWDoexfv161NTUwGw2Y/PmzdA0jfPMoJKNl8fjkW6OMUg0iL/97W8IBALYsWMHKisrsWXLFjz55JOZ7hZ1o729HQDw/PPPZ7gn9Gl++9vfYs+ePbDZbACAzZs3Y+XKlfjqV7+Kn/3sZ/j73/+OmTNnZriXFNN1vE6dOoUf/OAHWLp0aYZ7Rsns2bMHubm5eOSRR9Dc3Ixvf/vb+MIXvsA5ZmDJxuyuu+7iPDOw/fv3AwBefPFFHD16NB4kcp4ZU7Lxmj59unRzjI8cDOL48eOYPHkyAGDs2LGoqqrKcI/oSt5//334/X4sXboUS5YsQWVlZaa7RN0YNmwYHn/88fjr6upqXH/99QCAKVOm4MiRI5nqGiXRdbyqqqpw4MABLF68GPfffz+83sTDtClzbrnlFvz4xz+OvzabzZxjBpdszDjPjG3GjBnYuHEjAODjjz/GoEGDOM8MLNl4yTjHGCQahNfrhcPhiL82m80IhUIZ7BFdSb9+/bBs2TI888wz8WNZOF7GNGvWLKjq5UUTmqZBURQAgN1uh8fjyVTXKImu4zVmzBisWbMGL7zwAoYOHYpt27ZlsHfUld1uh8PhgNfrxT333IOVK1dyjhlcsjHjPDM+VVWxdu1abNy4EbNmzeI8M7iu4yXjHGOQaBAOhwM+ny/+OhKJdLpRImMpKSnBt771LSiKgpKSEuTm5sLtdme6W/QZdNyz4fP5kJOTk8He0KeZOXMmSktL4/9+6tSpDPeIujp37hyWLFmCefPm4Zvf/CbnmAS6jhnnmRy2bt2K119/HQ888EB82wvAeWZUHcerrKxMujnGINEgxo8fj4MHDwIAKisrMXLkyAz3iK5k586d2LJlCwCgoaEBXq8XLpcrw72iz+KLX/wijh49CgA4ePAgJk6cmOEe0ZUsW7YM7733HgCgoqICX/rSlzLcI+rowoULWLp0KVavXo3vfOc7ADjHjC7ZmHGeGdtf/vIXPPXUUwAAm80GRVFQWlrKeWZQycZrxYoV0s0xRdM0LdOdoMvVTc+cOQNN07Bp0yaMGDEi092ibgQCAdx33334+OOPoSgKVq1ahfHjx2e6W9SNuro6/OQnP8FLL72EmpoaPPDAAwgGgxg+fDjKy8thNpsz3UXqoON4VVdXY+PGjbBYLBg0aBA2btzYaWk+ZVZ5eTleffVVDB8+PN7205/+FOXl5ZxjBpVszFauXIlHHnmE88ygWltbcd999+HChQsIhUL40Y9+hBEjRvC3zKCSjdeQIUOk+y1jkEhERERERERxXG5KREREREREcQwSiYiIiIiIKI5BIhEREREREcUxSCQiIiIiIqI4BolEREREREQUxyCRiIhIpzNnzmDUqFF4/fXXO7VXVFTgtttuw6xZszBz5kzcc889OH/+fPy/jxo1CkD02I/S0lLMmzcvfsD59OnT8dhjj3W6ntfrxdy5c1FXVyf+QxERUZ+lZroDREREstu1axduueUW7NixA7NmzQIAHDt2DKtXr8YTTzyBsWPHAgBeeOEF3HXXXdi1a1fCNfLz87F79+7464aGBsyaNQtz5szBiBEjcPLkSaxfvx61tbVp+UxERNR3MZNIRESkQzAYxF//+lesXLkS1dXV+PDDDwEA27dvx5133hkPEAFg8eLFmD17NgKBwKde1+12Q9M02O12AMBLL72EDRs2ID8/X8wHISIiuoSZRCIiIh3efvttXHPNNSgpKcGMGTOwY8cOrF69GpWVlVi3bl3C+5ctW5b0Oo2NjZg3bx7a29vR3NyM0aNH44knnsDgwYMBAA8//LDQz0FERBTDTCIREZEOu3btwty5cwEAs2fPxp/+9Kd4plBRFABAIBCI7zecNm0a3n333YTrxJabvvLKK5g3bx40TcONN96Yvg9CRER0CYNEIiKiq9TU1IR33nkHv//97zF9+nSsX78eFy9exJtvvonRo0fHg0Gr1Yrdu3dj9+7dGDp0KILBYLfXNJlMWLNmDRoaGvDMM8+k66MQERHFMUgkIiK6Srt378bXvvY1HDx4EG+99Rb279+PO+64Ay+++CLuvvtubNu2DSdPnoy///3338dHH30Es9l8xeuqqoo1a9Zg+/btcLvdoj8GERFRJ9yTSEREdJX+/Oc/49577+3UtnjxYvzud79DXl4efvnLX+JXv/oVLly4gNbWVgwZMgRr167FxIkTP/XaU6ZMwbhx4/DrX/8a5eXloj4CERFRAkXTNC3TnSAiIiIiIiJj4HJTIiIiIiIiimOQSERERERERHEMEomIiIiIiCiOQSIRERERERHFMUgkIiIiIiKiOAaJREREREREFMcgkYiIiIiIiOIYJBIREREREVHc/wMgehHvSJ5lygAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c1d184c18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(color_codes=True)\n",
    "plt.figure(figsize=(15,20))\n",
    "\n",
    "plt.subplot(311)\n",
    "plt.title('Random Forests', fontsize = 17)\n",
    "plt.ylim(-10000, 10000)\n",
    "sns.regplot(data['AGIR1'], data['RF_p'], fit_reg=False)\n",
    "\n",
    "plt.subplot(312)\n",
    "plt.title('PUF Test', fontsize = 17)\n",
    "plt.ylim(-10000, 10000)\n",
    "sns.regplot(data['AGIR1'], data['P22250'], fit_reg=False)\n",
    "\n",
    "plt.subplot(313)\n",
    "plt.title('MNLogit + OLS', fontsize = 17)\n",
    "plt.ylim(-10000, 10000)\n",
    "sns.regplot(data['AGIR1'], data['mnlOLS_p'], fit_reg=False)\n",
    "\n",
    "plt.suptitle('In +/- 10,000', fontsize = 25)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}